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  • Computational Methods, Genomics  (67)
  • Marine Geosciences and Applied Geophysics  (27)
  • Natural Disasters
  • Pathogens & Pathogenicity
  • Oxford University Press  (107)
  • American Chemical Society (ACS)
  • Public Library of Science (PLoS)
  • 2010-2014  (107)
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  • Oxford University Press  (107)
  • American Chemical Society (ACS)
  • Public Library of Science (PLoS)
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  • 1
    Publication Date: 2013-09-26
    Description: Tandem repeats (TRs) are often present in proteins with crucial functions, responsible for resistance, pathogenicity and associated with infectious or neurodegenerative diseases. This motivates numerous studies of TRs and their evolution, requiring accurate multiple sequence alignment. TRs may be lost or inserted at any position of a TR region by replication slippage or recombination, but current methods assume fixed unit boundaries, and yet are of high complexity. We present a new global graph-based alignment method that does not restrict TR unit indels by unit boundaries. TR indels are modeled separately and penalized using the phylogeny-aware alignment algorithm. This ensures enhanced accuracy of reconstructed alignments, disentangling TRs and measuring indel events and rates in a biologically meaningful way. Our method detects not only duplication events but also all changes in TR regions owing to recombination, strand slippage and other events inserting or deleting TR units. We evaluate our method by simulation incorporating TR evolution, by either sampling TRs from a profile hidden Markov model or by mimicking strand slippage with duplications. The new method is illustrated on a family of type III effectors, a pathogenicity determinant in agriculturally important bacteria Ralstonia solanacearum. We show that TR indel rate variation contributes to the diversification of this protein family.
    Keywords: Computational Methods, Genomics
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  • 2
    Publication Date: 2013-06-08
    Description: The introduction of next generation sequencing methods in genome studies has made it possible to shift research from a gene-centric approach to a genome wide view. Although methods and tools to detect single nucleotide polymorphisms are becoming more mature, methods to identify and visualize structural variation (SV) are still in their infancy. Most genome browsers can only compare a given sequence to a reference genome; therefore, direct comparison of multiple individuals still remains a challenge. Therefore, the implementation of efficient approaches to explore and visualize SVs and directly compare two or more individuals is desirable. In this article, we present a visualization approach that uses space-filling Hilbert curves to explore SVs based on both read-depth and pair-end information. An interactive open-source Java application, called Meander , implements the proposed methodology, and its functionality is demonstrated using two cases. With Meander , users can explore variations at different levels of resolution and simultaneously compare up to four different individuals against a common reference. The application was developed using Java version 1.6 and Processing.org and can be run on any platform. It can be found at http://homes.esat.kuleuven.be/~bioiuser/meander .
    Keywords: Computational Methods, Genomics
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  • 3
    Publication Date: 2014-11-07
    Description: A new functional gene database, FOAM (Functional Ontology Assignments for Metagenomes), was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs). Sets of aligned protein sequences (i.e. ‘profiles’) were tailored to a large group of target KEGG Orthologs (KOs) from which HMMs were trained. The alignments were checked and curated to make them specific to the targeted KO. Within this process, sequence profiles were enriched with the most abundant sequences available to maximize the yield of accurate classifier models. An associated functional ontology was built to describe the functional groups and hierarchy. FOAM allows the user to select the target search space before HMM-based comparison steps and to easily organize the results into different functional categories and subcategories. FOAM is publicly available at http://portal.nersc.gov/project/m1317/FOAM/ .
    Keywords: Computational Methods, Genomics
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  • 4
    Publication Date: 2014-11-28
    Description: It is now known that unwanted noise and unmodeled artifacts such as batch effects can dramatically reduce the accuracy of statistical inference in genomic experiments. These sources of noise must be modeled and removed to accurately measure biological variability and to obtain correct statistical inference when performing high-throughput genomic analysis. We introduced surrogate variable analysis (sva) for estimating these artifacts by (i) identifying the part of the genomic data only affected by artifacts and (ii) estimating the artifacts with principal components or singular vectors of the subset of the data matrix. The resulting estimates of artifacts can be used in subsequent analyses as adjustment factors to correct analyses. Here I describe a version of the sva approach specifically created for count data or FPKMs from sequencing experiments based on appropriate data transformation. I also describe the addition of supervised sva (ssva) for using control probes to identify the part of the genomic data only affected by artifacts. I present a comparison between these versions of sva and other methods for batch effect estimation on simulated data, real count-based data and FPKM-based data. These updates are available through the sva Bioconductor package and I have made fully reproducible analysis using these methods available from: https://github.com/jtleek/svaseq .
    Keywords: Computational Methods, Genomics
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  • 5
    Publication Date: 2014-11-28
    Description: High-throughput techniques have considerably increased the potential of comparative genomics whilst simultaneously posing many new challenges. One of those challenges involves efficiently mining the large amount of data produced and exploring the landscape of both conserved and idiosyncratic genomic regions across multiple genomes. Domains of application of these analyses are diverse: identification of evolutionary events, inference of gene functions, detection of niche-specific genes or phylogenetic profiling. Insyght is a comparative genomic visualization tool that combines three complementary displays: (i) a table for thoroughly browsing amongst homologues, (ii) a comparator of orthologue functional annotations and (iii) a genomic organization view designed to improve the legibility of rearrangements and distinctive loci. The latter display combines symbolic and proportional graphical paradigms. Synchronized navigation across multiple species and interoperability between the views are core features of Insyght. A gene filter mechanism is provided that helps the user to build a biologically relevant gene set according to multiple criteria such as presence/absence of homologues and/or various annotations. We illustrate the use of Insyght with scenarios. Currently, only Bacteria and Archaea are supported. A public instance is available at http://genome.jouy.inra.fr/Insyght . The tool is freely downloadable for private data set analysis.
    Keywords: Computational Methods, Genomics
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  • 6
    Publication Date: 2014-11-28
    Description: The 54 promoters are unique in prokaryotic genome and responsible for transcripting carbon and nitrogen-related genes. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapidly and effectively identifying the 54 promoters. Here, a predictor called ‘ iPro54-PseKNC ’ was developed. In the predictor, the samples of DNA sequences were formulated by a novel feature vector called ‘pseudo k -tuple nucleotide composition’, which was further optimized by the incremental feature selection procedure. The performance of iPro54-PseKNC was examined by the rigorous jackknife cross-validation tests on a stringent benchmark data set. As a user-friendly web-server, iPro54-PseKNC is freely accessible at http://lin.uestc.edu.cn/server/iPro54-PseKNC . For the convenience of the vast majority of experimental scientists, a step-by-step protocol guide was provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics that were presented in this paper just for its integrity. Meanwhile, we also discovered through an in-depth statistical analysis that the distribution of distances between the transcription start sites and the translation initiation sites were governed by the gamma distribution, which may provide a fundamental physical principle for studying the 54 promoters.
    Keywords: Computational Methods, Genomics
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  • 7
    Publication Date: 2014-11-28
    Description: We present a discriminative learning method for pattern discovery of binding sites in nucleic acid sequences based on hidden Markov models. Sets of positive and negative example sequences are mined for sequence motifs whose occurrence frequency varies between the sets. The method offers several objective functions, but we concentrate on mutual information of condition and motif occurrence. We perform a systematic comparison of our method and numerous published motif-finding tools. Our method achieves the highest motif discovery performance, while being faster than most published methods. We present case studies of data from various technologies, including ChIP-Seq, RIP-Chip and PAR-CLIP, of embryonic stem cell transcription factors and of RNA-binding proteins, demonstrating practicality and utility of the method. For the alternative splicing factor RBM10, our analysis finds motifs known to be splicing-relevant. The motif discovery method is implemented in the free software package Discrover. It is applicable to genome- and transcriptome-scale data, makes use of available repeat experiments and aside from binary contrasts also more complex data configurations can be utilized.
    Keywords: Computational Methods, Genomics
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  • 8
    Publication Date: 2013-02-20
    Description: While it has been long recognized that genes are not randomly positioned along the genome, the degree to which its 3D structure influences the arrangement of genes has remained elusive. In particular, several lines of evidence suggest that actively transcribed genes are spatially co-localized, forming transcription factories; however, a generalized systematic test has hitherto not been described. Here we reveal transcription factories using a rigorous definition of genomic structure based on Saccharomyces cerevisiae chromosome conformation capture data, coupled with an experimental design controlling for the primary gene order. We develop a data-driven method for the interpolation and the embedding of such datasets and introduce statistics that enable the comparison of the spatial and genomic densities of genes. Combining these, we report evidence that co-regulated genes are clustered in space, beyond their observed clustering in the context of gene order along the genome and show this phenomenon is significant for 64 out of 117 transcription factors. Furthermore, we show that those transcription factors with high spatially co-localized targets are expressed higher than those whose targets are not spatially clustered. Collectively, our results support the notion that, at a given time, the physical density of genes is intimately related to regulatory activity.
    Keywords: Computational Methods, Genomics
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  • 9
    Publication Date: 2012-12-14
    Description: Pan-genome ortholog clustering tool ( PanOCT ) is a tool for pan-genomic analysis of closely related prokaryotic species or strains. PanOCT uses conserved gene neighborhood information to separate recently diverged paralogs into orthologous clusters where homology-only clustering methods cannot. The results from PanOCT and three commonly used graph-based ortholog-finding programs were compared using a set of four publicly available strains of the same bacterial species. All four methods agreed on ~70% of the clusters and ~86% of the proteins. The clusters that did not agree were inspected for evidence of correctness resulting in 85 high-confidence manually curated clusters that were used to compare all four methods.
    Keywords: Computational Methods, Genomics
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  • 10
    Publication Date: 2012-10-10
    Description: A novel ab initio parameter-tuning-free system to identify transcriptional factor (TF) binding motifs (TFBMs) in genome DNA sequences was developed. It is based on the comparison of two types of frequency distributions with respect to the TFBM candidates in the target DNA sequences and the non-candidates in the background sequence, with the latter generated by utilizing the intergenic sequences. For benchmark tests, we used DNA sequence datasets extracted by ChIP-on-chip and ChIP-seq techniques and identified 65 yeast and four mammalian TFBMs, with the latter including gaps. The accuracy of our system was compared with those of other available programs (i.e. MEME, Weeder, BioProspector, MDscan and DME) and was the best among them, even without tuning of the parameter set for each TFBM and pre-treatment/editing of the target DNA sequences. Moreover, with respect to some TFs for which the identified motifs are inconsistent with those in the references, our results were revealed to be correct, by comparing them with other existing experimental data. Thus, our identification system does not need any other biological information except for gene positions, and is also expected to be applicable to genome DNA sequences to identify unknown TFBMs as well as known ones.
    Keywords: Computational Methods, Genomics
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  • 11
    Publication Date: 2012-10-10
    Description: MicroRNAs (miRNAs) are major regulators of gene expression in multicellular organisms. They recognize their targets by sequence complementarity and guide them to cleavage or translational arrest. It is generally accepted that plant miRNAs have extensive complementarity to their targets and their prediction usually relies on the use of empirical parameters deduced from known miRNA–target interactions. Here, we developed a strategy to identify miRNA targets which is mainly based on the conservation of the potential regulation in different species. We applied the approach to expressed sequence tags datasets from angiosperms. Using this strategy, we predicted many new interactions and experimentally validated previously unknown miRNA targets in Arabidopsis thaliana . Newly identified targets that are broadly conserved include auxin regulators, transcription factors and transporters. Some of them might participate in the same pathways as the targets known before, suggesting that some miRNAs might control different aspects of a biological process. Furthermore, this approach can be used to identify targets present in a specific group of species, and, as a proof of principle, we analyzed Solanaceae -specific targets. The presented strategy can be used alone or in combination with other approaches to find miRNA targets in plants.
    Keywords: Computational Methods, Genomics
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  • 12
    Publication Date: 2012-04-15
    Description: We address the challenge of regulatory sequence alignment with a new method, Pro-Coffee, a multiple aligner specifically designed for homologous promoter regions. Pro-Coffee uses a dinucleotide substitution matrix estimated on alignments of functional binding sites from TRANSFAC. We designed a validation framework using several thousand families of orthologous promoters. This dataset was used to evaluate the accuracy for predicting true human orthologs among their paralogs. We found that whereas other methods achieve on average 73.5% accuracy, and 77.6% when trained on that same dataset, the figure goes up to 80.4% for Pro-Coffee. We then applied a novel validation procedure based on multi-species ChIP-seq data. Trained and untrained methods were tested for their capacity to correctly align experimentally detected binding sites. Whereas the average number of correctly aligned sites for two transcription factors is 284 for default methods and 316 for trained methods, Pro-Coffee achieves 331, 16.5% above the default average. We find a high correlation between a method's performance when classifying orthologs and its ability to correctly align proven binding sites. Not only has this interesting biological consequences, it also allows us to conclude that any method that is trained on the ortholog data set will result in functionally more informative alignments.
    Keywords: Computational Methods, Genomics
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  • 13
    Publication Date: 2012-04-15
    Description: MCScan is an algorithm able to scan multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and align these regions using genes as anchors. The MCScanX toolkit implements an adjusted MCScan algorithm for detection of synteny and collinearity that extends the original software by incorporating 14 utility programs for visualization of results and additional downstream analyses. Applications of MCScanX to several sequenced plant genomes and gene families are shown as examples. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families. The source code and documentation of MCScanX are freely available at http://chibba.pgml.uga.edu/mcscan2/ .
    Keywords: Computational Methods, Genomics
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  • 14
    Publication Date: 2012-07-22
    Description: Cytosines in genomic DNA are sometimes methylated. This affects many biological processes and diseases. The standard way of measuring methylation is to use bisulfite, which converts unmethylated cytosines to thymines, then sequence the DNA and compare it to a reference genome sequence. We describe a method for the critical step of aligning the DNA reads to the correct genomic locations. Our method builds on classic alignment techniques, including likelihood-ratio scores and spaced seeds. In a realistic benchmark, our method has a better combination of sensitivity, specificity and speed than nine other high-throughput bisulfite aligners. This study enables more accurate and rational analysis of DNA methylation. It also illustrates how to adapt general-purpose alignment methods to a special case with distorted base patterns: this should be informative for other special cases such as ancient DNA and AT-rich genomes.
    Keywords: Computational Methods, Genomics
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  • 15
    Publication Date: 2012-09-13
    Description: Prophages are phages in lysogeny that are integrated into, and replicated as part of, the host bacterial genome. These mobile elements can have tremendous impact on their bacterial hosts’ genomes and phenotypes, which may lead to strain emergence and diversification, increased virulence or antibiotic resistance. However, finding prophages in microbial genomes remains a problem with no definitive solution. The majority of existing tools rely on detecting genomic regions enriched in protein-coding genes with known phage homologs, which hinders the de novo discovery of phage regions. In this study, a weighted phage detection algorithm, PhiSpy was developed based on seven distinctive characteristics of prophages, i.e. protein length, transcription strand directionality, customized AT and GC skew, the abundance of unique phage words, phage insertion points and the similarity of phage proteins. The first five characteristics are capable of identifying prophages without any sequence similarity with known phage genes. PhiSpy locates prophages by ranking genomic regions enriched in distinctive phage traits, which leads to the successful prediction of 94% of prophages in 50 complete bacterial genomes with a 6% false-negative rate and a 0.66% false-positive rate.
    Keywords: Computational Methods, Genomics
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  • 16
    Publication Date: 2012-06-06
    Description: Messenger RNA sequences possess specific nucleotide patterns distinguishing them from non-coding genomic sequences. In this study, we explore the utilization of modified Markov models to analyze sequences up to 44 bp, far beyond the 8-bp limit of conventional Markov models, for exon/intron discrimination. In order to analyze nucleotide sequences of this length, their information content is first reduced by conversion into shorter binary patterns via the application of numerous abstraction schemes. After the conversion of genomic sequences to binary strings, homogenous Markov models trained on the binary sequences are used to discriminate between exons and introns. We term this approach the Binary Abstraction Markov Model (BAMM). High-quality abstraction schemes for exon/intron discrimination are selected using optimization algorithms on supercomputers. The best MM classifiers are then combined using support vector machines into a single classifier. With this approach, over 95% classification accuracy is achieved without taking reading frame into account. With further development, the BAMM approach can be applied to sequences lacking the genetic code such as ncRNAs and 5'-untranslated regions.
    Keywords: Computational Methods, Genomics
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  • 17
    Publication Date: 2012-05-13
    Description: Insertional mutagenesis screens in mice are used to identify individual genes that drive tumor formation. In these screens, candidate cancer genes are identified if their genomic location is proximal to a common insertion site (CIS) defined by high rates of transposon or retroviral insertions in a given genomic window. In this article, we describe a new method for defining CISs based on a Poisson distribution, the Poisson Regression Insertion Model, and show that this new method is an improvement over previously described methods. We also describe a modification of the method that can identify pairs and higher orders of co-occurring common insertion sites. We apply these methods to two data sets, one generated in a transposon-based screen for gastrointestinal tract cancer genes and another based on the set of retroviral insertions in the Retroviral Tagged Cancer Gene Database. We show that the new methods identify more relevant candidate genes and candidate gene pairs than found using previous methods. Identification of the biologically relevant set of mutations that occur in a single cell and cause tumor progression will aid in the rational design of single and combinatorial therapies in the upcoming age of personalized cancer therapy.
    Keywords: Computational Methods, Genomics
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  • 18
    Publication Date: 2011-11-24
    Description: Looking into the future of agriculture raises three challenging questions: How can agriculture deal with an uncertain future? How do local vulnerabilities and global disparities respond to this uncertain future? How should we prioritise adaptation to overcome the resulting future risks? This paper analyses the broad question of how climate change science may provide some insights into these issues. The data provided for the analysis are the product of our new research on global impacts of climate change in agriculture. The questions are analysed across world regions to provide some thoughts on policy development.
    Keywords: N50 - General, International, or Comparative, Q18 - Agricultural Policy ; Food Policy, Q54 - Climate ; Natural Disasters ; Global Warming
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 19
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    Oxford University Press
    Publication Date: 2014-01-22
    Description: This literature review focuses on the relationships between population, poverty, and climate change. Developed countries are largely responsible for global warming, but the brunt of the fallout will be borne by developing countries in forms such as lower agricultural output, poorer health, and more frequent natural disasters. Although carbon emissions per capita have leveled off in developed countries, they are projected to rise rapidly in developing countries because of economic growth and population growth. Unfortunately, the latter will rise most notably in the poorest countries, combining with climate change to slow poverty reduction. These countries have many incentives to lower fertility. Previous studies indicate that in high fertility settings, fertility decline facilitates economic growth and poverty reduction. It also reduces the pressure on livelihoods and frees resources that can be used to cope with climate change. Moreover, slowing population growth helps avert some of the projected global warming, which will benefit the poorest countries far more than it will benefit developed countries that lie at higher latitudes and/or have more resources to cope with climate change. Natural experiments indicate that family-planning programs are effective and highly pro-poor in their impact. While the rest of the world wrestles with the complexities of reducing emissions, the poorest countries will benefit from simple programs to lower fertility.
    Keywords: Q56 - Environment and Development ; Environment and Trade ; Sustainability ; Environmental Accounting ; , Q54 - Climate ; Natural Disasters ; Global Warming, J13 - Fertility ; Family Planning ; Child Care ; Children ; Youth, J18 - Public Policy
    Print ISSN: 0257-3032
    Electronic ISSN: 1564-6971
    Topics: Economics
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  • 20
    Publication Date: 2014-05-01
    Description: Molecular stratification of tumors is essential for developing personalized therapies. Although patient stratification strategies have been successful; computational methods to accurately translate the gene-signature from high-throughput platform to a clinically adaptable low-dimensional platform are currently lacking. Here, we describe PIGExClass (platform-independent isoform-level gene-expression based classification-system), a novel computational approach to derive and then transfer gene-signatures from one analytical platform to another. We applied PIGExClass to design a reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) based molecular-subtyping assay for glioblastoma multiforme (GBM), the most aggressive primary brain tumors. Unsupervised clustering of TCGA (the Cancer Genome Altas Consortium) GBM samples, based on isoform-level gene-expression profiles, recaptured the four known molecular subgroups but switched the subtype for 19% of the samples, resulting in significant ( P = 0.0103) survival differences among the refined subgroups. PIGExClass derived four-class classifier, which requires only 121 transcript-variants, assigns GBM patients’ molecular subtype with 92% accuracy. This classifier was translated to an RT-qPCR assay and validated in an independent cohort of 206 GBM samples. Our results demonstrate the efficacy of PIGExClass in the design of clinically adaptable molecular subtyping assay and have implications for developing robust diagnostic assays for cancer patient stratification.
    Keywords: Computational Methods, Genomics
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  • 21
    Publication Date: 2014-05-01
    Description: The ability to correlate chromosome conformation and gene expression gives a great deal of information regarding the strategies used by a cell to properly regulate gene activity. 4C-Seq is a relatively new and increasingly popular technology where the set of genomic interactions generated by a single point in the genome can be determined. 4C-Seq experiments generate large, complicated data sets and it is imperative that signal is properly distinguished from noise. Currently, there are a limited number of methods for analyzing 4C-Seq data. Here, we present a new method, fourSig , which in addition to being precise and simple to use also includes a new feature that prioritizes detected interactions. Our results demonstrate the efficacy of fourSig with previously published and novel 4C-Seq data sets and show that our significance prioritization correlates with the ability to reproducibly detect interactions among replicates.
    Keywords: Computational Methods, Genomics
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  • 22
    Publication Date: 2014-04-03
    Description: Alternative transcript processing is an important mechanism for generating functional diversity in genes. However, little is known about the precise functions of individual isoforms. In fact, proteins (translated from transcript isoforms), not genes, are the function carriers. By integrating multiple human RNA-seq data sets, we carried out the first systematic prediction of isoform functions, enabling high-resolution functional annotation of human transcriptome. Unlike gene function prediction, isoform function prediction faces a unique challenge: the lack of the training data—all known functional annotations are at the gene level. To address this challenge, we modelled the gene–isoform relationships as multiple instance data and developed a novel label propagation method to predict functions. Our method achieved an average area under the receiver operating characteristic curve of 0.67 and assigned functions to 15 572 isoforms. Interestingly, we observed that different functions have different sensitivities to alternative isoform processing, and that the function diversity of isoforms from the same gene is positively correlated with their tissue expression diversity. Finally, we surveyed the literature to validate our predictions for a number of apoptotic genes. Strikingly, for the famous ‘TP53’ gene, we not only accurately identified the apoptosis regulation function of its five isoforms, but also correctly predicted the precise direction of the regulation.
    Keywords: Computational Methods, Genomics
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  • 23
    Publication Date: 2014-04-05
    Description: It appears that news media and some pro-environmental organizations have the tendency to accentuate or even exaggerate the damage caused by climate change. This article provides a rationale for this tendency by using a modified International Environmental Agreement (IEA) model with asymmetric information. We find that the information manipulation has an instrumental value, as it ex post induces more countries to participate in an IEA, which will eventually enhance global welfare. From the ex ante perspective, however, the impact that manipulating information has on the level of participation in an IEA and on welfare is ambiguous.
    Keywords: D82 - Asymmetric and Private Information, L82 - Entertainment ; Media, Q54 - Climate ; Natural Disasters ; Global Warming
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 24
    Publication Date: 2012-03-29
    Description: Broadly, computational approaches for ortholog assignment is a three steps process: (i) identify all putative homologs between the genomes, (ii) identify gene anchors and (iii) link anchors to identify best gene matches given their order and context. In this article, we engineer two methods to improve two important aspects of this pipeline [specifically steps (ii) and (iii)]. First, computing sequence similarity data [step (i)] is a computationally intensive task for large sequence sets, creating a bottleneck in the ortholog assignment pipeline. We have designed a fast and highly scalable sort-join method (afree) based on k -mer counts to rapidly compare all pairs of sequences in a large protein sequence set to identify putative homologs. Second, availability of complex genomes containing large gene families with prevalence of complex evolutionary events, such as duplications, has made the task of assigning orthologs and co-orthologs difficult. Here, we have developed an iterative graph matching strategy where at each iteration the best gene assignments are identified resulting in a set of orthologs and co-orthologs. We find that the afree algorithm is faster than existing methods and maintains high accuracy in identifying similar genes. The iterative graph matching strategy also showed high accuracy in identifying complex gene relationships. Standalone afree available from http://vbc.med.monash.edu.au/~kmahmood/afree . EGM2, complete ortholog assignment pipeline (including afree and the iterative graph matching method) available from http://vbc.med.monash.edu.au/~kmahmood/EGM2 .
    Keywords: Computational Methods, Genomics
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  • 25
    Publication Date: 2012-03-29
    Description: With the availability of next-generation sequencing (NGS) technology, it is expected that sequence variants may be called on a genomic scale. Here, we demonstrate that a deeper understanding of the distribution of the variant call frequencies at heterozygous loci in NGS data sets is a prerequisite for sensitive variant detection. We model the crucial steps in an NGS protocol as a stochastic branching process and derive a mathematical framework for the expected distribution of alleles at heterozygous loci before measurement that is sequencing. We confirm our theoretical results by analyzing technical replicates of human exome data and demonstrate that the variance of allele frequencies at heterozygous loci is higher than expected by a simple binomial distribution. Due to this high variance, mutation callers relying on binomial distributed priors are less sensitive for heterozygous variants that deviate strongly from the expected mean frequency. Our results also indicate that error rates can be reduced to a greater degree by technical replicates than by increasing sequencing depth.
    Keywords: Computational Methods, Genomics
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  • 26
    Publication Date: 2012-03-14
    Description: An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis.
    Keywords: Computational Methods, Genomics
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  • 27
    Publication Date: 2012-02-17
    Description: We introduce the software tool NTRFinder to search for a complex repetitive structure in DNA we call a nested tandem repeat (NTR). An NTR is a recurrence of two or more distinct tandem motifs interspersed with each other. We propose that NTRs can be used as phylogenetic and population markers. We have tested our algorithm on both real and simulated data, and present some real NTRs of interest. NTRFinder can be downloaded from http://www.maths.otago.ac.nz/~aamatroud/ .
    Keywords: Computational Methods, Genomics
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  • 28
    Publication Date: 2014-10-10
    Description: Parallel analysis of RNA ends (PARE) is a technique utilizing high-throughput sequencing to profile uncapped, mRNA cleavage or decay products on a genome-wide basis. Tools currently available to validate miRNA targets using PARE data employ only annotated genes, whereas important targets may be found in unannotated genomic regions. To handle such cases and to scale to the growing availability of PARE data and genomes, we developed a new tool, ‘ sPARTA ’ (small RNA-PARE target analyzer) that utilizes a built-in, plant-focused target prediction module (aka ‘ miRferno ’). sPARTA not only exhibits an unprecedented gain in speed but also it shows greater predictive power by validating more targets, compared to a popular alternative. In addition, the novel ‘seed-free’ mode, optimized to find targets irrespective of complementarity in the seed-region, identifies novel intergenic targets. To fully capitalize on the novelty and strengths of sPARTA , we developed a web resource, ‘ comPARE ’, for plant miRNA target analysis; this facilitates the systematic identification and analysis of miRNA-target interactions across multiple species, integrated with visualization tools. This collation of high-throughput small RNA and PARE datasets from different genomes further facilitates re-evaluation of existing miRNA annotations, resulting in a ‘cleaner’ set of microRNAs.
    Keywords: Computational Methods, Genomics
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  • 29
    Publication Date: 2014-10-10
    Description: Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions.
    Keywords: Computational Methods, Genomics
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  • 30
    Publication Date: 2014-10-10
    Description: Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1 090 698 and 10 625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface.
    Keywords: Computational Methods, Genomics
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  • 31
    Publication Date: 2014-11-02
    Description: Passive interferometry technology is based on the relation between the reflection and the transmission responses of the subsurface. The transmission response can be received at surface in the presence of the ambient noise source in the subsurface with the cross-correlation (CC) or multidimensional deconvolution methods. We investigate the feasibility of electromagnetic (EM) wave passive interferometry with CC method. We design a 2-D finite-difference time domain (FDTD) algorithm to simulate the long-duration ground penetrating radar (GPR) measurements with random distribution of passive EM sources. The noise sources have random duration time, waveform and spatial distribution. We test the FDTD GPR passive interferometry code with above source characteristics and apply the method to light non-aqueous phase liquid (LNAPL) monitoring. Based on the model simulation data, by using common midpoint velocity analysis and normal move out correction to process the interferometry retrieve record, we can accurately obtain the dynamic changing characteristics of the target's permittivity. The LNAPL dynamic leakage model can be imaged as well. The synthetic results demonstrate that the GPR passive interferometry is feasible in subsurface LNAPL monitoring. Our work provides a foundation for a passive interferometry field application using GPR.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 32
    Publication Date: 2014-10-23
    Description: 3-D electrical resistivity surveys and inversion models are required to accurately resolve structures in areas with very complex geology where 2-D models might suffer from artefacts. Many 3-D surveys use a grid where the number of electrodes along one direction ( x ) is much greater than in the perpendicular direction ( y ). Frequently, due to limitations in the number of independent electrodes in the multi-electrode system, the surveys use a roll-along system with a small number of parallel survey lines aligned along the x -direction. The ‘Compare R’ array optimization method previously used for 2-D surveys is adapted for such 3-D surveys. Offset versions of the inline arrays used in 2-D surveys are included in the number of possible arrays (the comprehensive data set) to improve the sensitivity to structures in between the lines. The array geometric factor and its relative error are used to filter out potentially unstable arrays in the construction of the comprehensive data set. Comparisons of the conventional (consisting of dipole-dipole and Wenner–Schlumberger arrays) and optimized arrays are made using a synthetic model and experimental measurements in a tank. The tests show that structures located between the lines are better resolved with the optimized arrays. The optimized arrays also have significantly better depth resolution compared to the conventional arrays.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 33
    Publication Date: 2014-10-23
    Description: We apply a reversible-jump Markov chain Monte Carlo method to sample the Bayesian posterior model probability density function of 2-D seafloor resistivity as constrained by marine controlled source electromagnetic data. This density function of earth models conveys information on which parts of the model space are illuminated by the data. Whereas conventional gradient-based inversion approaches require subjective regularization choices to stabilize this highly non-linear and non-unique inverse problem and provide only a single solution with no model uncertainty information, the method we use entirely avoids model regularization. The result of our approach is an ensemble of models that can be visualized and queried to provide meaningful information about the sensitivity of the data to the subsurface, and the level of resolution of model parameters. We represent models in 2-D using a Voronoi cell parametrization. To make the 2-D problem practical, we use a source–receiver common midpoint approximation with 1-D forward modelling. Our algorithm is transdimensional and self-parametrizing where the number of resistivity cells within a 2-D depth section is variable, as are their positions and geometries. Two synthetic studies demonstrate the algorithm's use in the appraisal of a thin, segmented, resistive reservoir which makes for a challenging exploration target. As a demonstration example, we apply our method to survey data collected over the Scarborough gas field on the Northwest Australian shelf.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 34
    Publication Date: 2014-10-23
    Description: Compressional and shear wave seismic measurements were performed in an old railway tunnel and in galleries excavated in a 250-m-thick Toarcian claystone formation in the Tournemire experimental station (France). Three component (3C) geophones and three orthogonal orientations of the vibroseismic force source were used. Additionally, vertical seismic profiling (VSP) measurements were recorded with a 3C borehole geophone, a hydrophone and a microphone in a 159 m deep borehole (ID180) in the tunnel. The seismic data show that Toarcian claystone has strong transverse isotropy (TI) with a vertical symmetry axis. The qP , SH and qSV wave propagation velocities in horizontal directions—the plane of isotropy of the TI medium—are measured as 3550, 1850 and 1290 m s –1 , respectively. The zero-offset VSP reveals that only one shear wave propagates in the vertical (depth) direction and the P - and S -wave velocities are 3100 and 1375 m s –1 , respectively. Four elastic moduli of the TI medium are determined from the seismic velocities and from the bulk density of 2.53 g cm –3 : c 11 = 31.9 GPa, c 33 = 24.3 GPa, c 44 = 4.5 GPa and c 66 = 8.7 GPa. A walkaway VSP with the borehole geophone at 50 m depth in borehole ID180 and shot points in the galleries leads to oblique seismic ray paths which allow us to determine the fifth elastic modulus of the TI medium to c 13 = 16 GPa. The tube wave recorded by a hydrophone in the water filled lower part of the borehole propagates with 1350 m s –1 , which confirms the estimate of the elastic constant c 66 . The analysis of body wave and surface wave data from a seismic experiment in Galerie Est shows reflections from several fracture zones in the gallery floor. The thickness of the excavation damaged zone (EDZ) in the floor of Galerie Est is estimated to 0.7 m.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 35
    Publication Date: 2014-09-27
    Description: The Tonga-Kermadec forearc is deforming in response to on-going subduction of the Pacific Plate beneath the Indo-Australian Plate. Previous research has focussed on the structural development of the forearc where large bathymetric features such as the Hikurangi Plateau and Louisville Ridge seamount chain are being subducted. Consequently, knowledge of the ‘background’ forearc in regions of normal plate convergence is limited. We report on an ~250-km-long multichannel seismic reflection profile that was shot perpendicular to the Tonga-Kermadec trench at ~28°S to determine the lateral and temporal variations in the structure, stratigraphy and deformation of the Kermadec forearc resulting solely from Pacific Plate subduction. Interpretation of the seismic profile, in conjunction with regional swath bathymetry data, shows that the Pacific Plate exhibits horst and graben structures that accommodate bending-induced extensional stresses, generated as the trenchward dip of the crust increases. Trench infill is also much thicker than expected at 1 km which, we propose, results from increased sediment flux into and along the trench. Pervasive normal faulting of the mid-trench slope most likely accommodates the majority of the observed forearc extension in response to basal subduction erosion, and a structural high is located between the mid- and upper-trench slopes. We interpret this high as representing a dense and most likely structurally robust region of crust lying beneath this region. Sediment of the upper-trench slope documents depositional hiatuses and on-going uplift of the arc. Strong along-arc currents appear to erode the Kermadec volcanic arc and distribute this sediment to the surrounding basins, while currents over the forearc redistribute deposits as sediment waves. Minor uplift of the transitional Kermadec forearc, observed just to the north of the profile, appears to relate to an underlying structural trend as well as subduction of the Louisville Ridge seamount chain 250 km to the north. Relative uplift of the Kermadec arc is observed from changes in the tilt of upper-trench slope deposits and extensional faulting of the basement immediately surrounding the Louisville Ridge.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 36
    Publication Date: 2014-11-28
    Description: Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE ( http://mips.helmholtz-muenchen.de/cogere ), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient 2 (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research.
    Keywords: Computational Methods, Genomics
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  • 37
    Publication Date: 2014-12-17
    Description: Non-coding RNAs (ncRNAs) are known to play important functional roles in the cell. However, their identification and recognition in genomic sequences remains challenging. In silico methods, such as classification tools, offer a fast and reliable way for such screening and multiple classifiers have already been developed to predict well-defined subfamilies of RNA. So far, however, out of all the ncRNAs, only tRNA, miRNA and snoRNA can be predicted with a satisfying sensitivity and specificity. We here present ptRNApred , a tool to detect and classify subclasses of non-coding RNA that are involved in the regulation of post-transcriptional modifications or DNA replication, which we here call post-transcriptional RNA (ptRNA). It (i) detects RNA sequences coding for post-transcriptional RNA from the genomic sequence with an overall sensitivity of 91% and a specificity of 94% and (ii) predicts ptRNA-subclasses that exist in eukaryotes: snRNA, snoRNA, RNase P, RNase MRP, Y RNA or telomerase RNA. AVAILABILITY: The ptRNApred software is open for public use on http://www.ptrnapred.org/ .
    Keywords: Computational Methods, Genomics
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  • 38
    Publication Date: 2014-12-17
    Description: Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6–96.8% precision and 91.6–95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/ .
    Keywords: Computational Methods, Genomics
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  • 39
    Publication Date: 2014-12-12
    Description: New methods are required to combine the information contained in the passive electrical and seismic signals to detect, localize and monitor hydromechanical disturbances in porous media. We propose a field experiment showing how passive seismic and electrical data can be combined together to detect a preferential flow path associated with internal erosion in a Earth dam. Continuous passive seismic and electrical (self-potential) monitoring data were recorded during a 7-d full-scale levee (earthen embankment) failure test, conducted in Booneschans, Netherlands in 2012. Spatially coherent acoustic emissions events and the development of a self-potential anomaly, associated with induced concentrated seepage and internal erosion phenomena, were identified and imaged near the downstream toe of the embankment, in an area that subsequently developed a series of concentrated water flows and sand boils, and where liquefaction of the embankment toe eventually developed. We present a new 4-D grid-search algorithm for acoustic emissions localization in both time and space, and the application of the localization results to add spatially varying constraints to time-lapse 3-D modelling of self-potential data in the terms of source current localization. Seismic signal localization results are utilized to build a set of time-invariant yet spatially varying model weights used for the inversion of the self-potential data. Results from the combination of these two passive techniques show results that are more consistent in terms of focused ground water flow with respect to visual observation on the embankment. This approach to geophysical monitoring of earthen embankments provides an improved approach for early detection and imaging of the development of embankment defects associated with concentrated seepage and internal erosion phenomena. The same approach can be used to detect various types of hydromechanical disturbances at larger scales.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 40
    Publication Date: 2014-10-12
    Description: We propose a two-phase damage theory in a viscoelastic medium to study the pressure and porosity diffusion in fractured near-surface porous rocks. The key ingredient in the viscoelastic theory is that the pressure difference between solid and fluid is divided into three parts, which contribute to reversible elastic potential energy, irreversible viscous entropy production and surface energy stored during deformation. The resulting continuum description of weakening and failure (distributed void generation and microcracking) in a linear Kelvin body accounts for surface energy being created by both viscous and elastic deformational work. The model shows that while non-linear permeability models leads to an enhanced diffusivity, damage makes the matrix more compressible if we assume the geometry/size of cracks remain unchanged. The net effect is that the porosity diffusivity is reduced causing fluid infiltration to accumulate closer to the injection source, leading to a slower fluid diffusion during hydraulic fracturing with a fixed porosity boundary condition. However if a constant overpressure boundary condition is applied, a weakened matrix with damage leads to greater pressure diffusivity than for porosity.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 41
    Publication Date: 2014-10-16
    Description: We define an algorithm in the time domain for computing the unwrapped instantaneous phase and its derivative, the instantaneous frequency, using only derivatives and integrals. It does not require user-defined parameters, like most algorithms proposed so far. We validate and compare its performance with respect to open-source and commercial software by synthetic and real data examples.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 42
    Publication Date: 2014-09-27
    Description: Simulating electromagnetic fields in the quasi-static regime by solving Maxwell's equations is a central task in many geophysical applications. In most cases, geophysical targets of interest exhibit complex topography and bathymetry as well as layers and faults. Capturing these effects with a sufficient level of detail is a huge challenge for numerical simulations. Standard techniques require a very fine discretization that can result in an impracticably large linear system to be solved. A remedy is to use locally refined and adaptive meshes, however, the potential coarsening is limited in the presence of highly heterogeneous and anisotropic conductivities. In this paper, we discuss the application of multiscale finite volume (MSFV) methods to Maxwell's equations in frequency domain. Given a partition of the fine mesh into a coarse mesh the idea is to obtain coarse-to-fine interpolation by solving local versions of Maxwell's equations on each coarsened grid cell. By construction, the interpolation accounts for fine scale conductivity changes, yields a natural homogenization, and reduces the fine mesh problem dramatically in size. To improve the accuracy for singular sources, we use an irregular coarsening strategy. We show that using MSFV methods we can simulate electromagnetic fields with reasonable accuracy in a fraction of the time as compared to state-of-the-art solvers for the fine mesh problem, especially when considering parallel platforms.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 43
    Publication Date: 2014-06-21
    Description: Wave-equation tomography (WT) and full waveform inversion (FWI) are combined through a hybrid misfit function to estimate high-resolution subsurface structures starting from a poorly constrained initial velocity model. Both methods share the same wavefield forward modelling and inversion schemes, while they differ only on the ways to calculate misfit functions and hence the ways to sample in the model space. Aiming at minimizing the cross-correlation phase delay between synthetic and real data, WT can be used to retrieve the long- and middle-wavelength model components, which are essential to FWI. Compared to ray-based traveltime tomography that is based on asymptotic high-frequency approximation, WT provides a better resolution by exploring the band-limited feature of seismic wavefield. On the other hand, FWI is capable of resolving the short-wavelength model component, complementing the WT. In this study, we apply WT to surface first-arrival refraction data, and apply FWI to both refraction and reflection data. We assign adaptive weights to the two different misfit measurements and build a progressive inversion strategy. To illustrate the advantage of our strategy over conventional ‘ray tomography + FWI’ approach, we show in a synthetic lens test that WT can provide extra subsurface information that is critical for a successful FWI application. To further show the efficiency, we test our strategy on the 2-D Marmousi model where satisfactory inversion results are achieved without much manual intervention. Finally, we apply the inversion strategy to a deep-water seismic data set acquired offshore Sumatra with a 12-km-long streamer. In order to alleviate several practical problems posed by the deep-water setting, we apply downward continuation (DC) to generate a virtual ocean bottom experiment data set prior to inversion. The new geometry after DC boosts up the shallow refractions, as well as avoiding cumbersome modelling through the thick water column, thus reducing the computation cost by 85 per cent. The inversion result from the new data set shows high-resolution shallow sediment structures and the migration images prove the superiority of the inverted model over a conventional tomography model.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 44
    Publication Date: 2014-06-21
    Description: The activation of Late Quaternary faults in the Central Apennines (Italy) could generate earthquakes with magnitude of about 6.5, and the Monte Vettore fault system probably belongs to the same category of seismogenetic faults. Such structure has been defined ‘silent’, because of its geological and geomorphological evidences of past activation, but the absence of historical records in the seismic catalogues to be associated with its activation. The ‘Piano di Castelluccio’ intramountain basin, resulting from the Quaternary activity of normal faults, is characterized by a secondary fault strand highlighted by a NW–SE fault scarp: it has been already studied through palaeoseismological trenches, which highlighted evidences of Quaternary shallow faulting due to strong earthquakes, and through a 2-D ground penetrating radar (GPR) survey, showing the first geophysical signature of faulting for this site. Within the same place, a 3-D GPR volume over a 20 20 m area has been collected. The collection of radar echoes in three dimensions allows to map both the vertical and lateral continuity of shallow geometries of the fault zone (Fz), imaging features with high resolution, ranging from few metres to centimetres and therefore imaging also local variations at the microscale. Several geophysical markers of faulting, already highlighted on this site, have been taken as reference to plan the 3-D survey. In this paper, we provide the first 3-D subsurface imaging of an active shallow fault belonging to the Umbria-Marche Apennine highlighting the subsurface fault geometry and the stratigraphic sequence up to a depth of about 5 m. From our data, geophysical faulting signatures are clearly visible in three dimensions: diffraction hyperbolas, truncations of layers, local attenuated zones and varying dip of the layers have been detected within the Fz. The interpretation of the 3-D data set provided qualitative and quantitative geological information in addition to the fault location, like its geometry, boundaries and an estimation of the fault throw.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 45
    Publication Date: 2014-07-03
    Description: In this paper, after a review of the evolution of the literature on climate change economics in agriculture, I present some evidence of the impact of different moments of the distribution of rainfall on farmers risk aversion. It is found that while more rainfall is negatively associated with the probability of observing risk aversion, rainfall variability is positively correlated. This result highlights an important behavioural dimension of climatic factors.
    Keywords: Q54 - Climate ; Natural Disasters ; Global Warming, Q56 - Environment and Development ; Environment and Trade ; Sustainability ; Environmental Accounting
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 46
    Publication Date: 2014-06-21
    Description: To estimate the seismic hazard, the geometry (dip, length and orientation) and the dynamics (type of displacements and amplitude) of the faults in the area of interest need to be understood. In this paper, in addition to geomorphologic observations, we present the results of two ground penetrating radar (GPR) campaigns conducted in 2010 and 2011 along the Emeelt fault in the vicinity of Ulaanbaatar, capital of Mongolia, located in an intracontinental region with low deformation rate that induces long recurrence time between large earthquakes. As the geomorphology induced by the fault activity has been highly smoothed by erosion processes since the last event, the fault location and geometry is difficult to determine precisely. However, by using GPR first, a non-destructive and fast investigation, the fault and the sedimentary deposits near the surface can be characterized and the results can be used for the choice of trench location. GPR was performed with a 50 MHz antenna over 2-D lines and with a 500 MHz antenna for pseudo-3-D surveys. The 500 MHz GPR profiles show a good consistency with the trench observations, dug next to the pseudo-3-D surveys. The 3-D 500 MHz GPR imaging of a palaeochannel crossed by the fault allowed us to estimate its lateral displacement to be about 2 m. This is consistent with a right lateral strike-slip displacement induced by an earthquake around magnitude 7 or several around magnitude 6. The 2-D 50 MHz profiles, recorded perpendicular to the fault, show a strong reflection dipping to the NE, which corresponds to the fault plane. Those profiles provided complementary information on the fault such as its location at shallow depth, its dip angle (from 23° to 35°) and define its lateral extension.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 47
    Publication Date: 2014-06-21
    Description: A new method to obtain the statistics of a geostatistical model is introduced. The method elicits the statistical information from a geological expert directly, by iteratively updating a population of vectors of statistics, based on the expert's subjective opinion of the corresponding geological simulations. Thus, it does not require the expert to have knowledge of the mathematical and statistical details of the model. The process uses a genetic algorithm to generate new vectors. We demonstrate the methodology for a particular geostatistical model used to model rock pore-space, which simulates the spatial distribution of matrix and pores over a 2-D grid, using multipoint statistics specified by conditional probabilities. Experts were asked to use the algorithm to estimate the statistics of a given target pore-space image with known statistics; thus, their numerical rates of convergence could be calculated. Convergence was measured for all experts, showing that the algorithm can be used to find appropriate probabilities given the expert's subjective input. However, considerable and apparently irreducible residual misfit was found between the true statistics and the estimates of statistics obtained by the experts, with the root-mean-square error on the conditional probabilities typically 〉0.1. This is interpreted as the limit of the experts’ abilities to distinguish between realizations of different spatial statistics using the algorithm. More accurate discrimination is therefore likely to require complementary elicitation techniques or sources of information independent of expert opinion.
    Keywords: Marine Geosciences and Applied Geophysics
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    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 48
    Publication Date: 2014-06-21
    Description: We show analytically that a well-known transfer function previously derived for the scalar acoustic problem that converts measurements from a 3-D (real-world) setting to a 2-D equivalent is directly applicable to the vector electromagnetic borehole ground penetrating radar problem. We also show that the transfer function's precision is improved for the low-loss case through the use of complex velocity. The transfer function has a strong effect on amplitude, and is therefore a critical preprocessing step for 2-D full-wave inversion when finding conductivity is of concern. We demonstrate the effectiveness of the transfer function through various numerical experiments and a synthetic frequency-domain full-wave inversion. We also compare the effectiveness of this curved-ray transfer function to a quasi-straight-ray transfer function. The inversion demonstrates the positive effect the transfer functions have on recovering conductivity and also that they are effective even when there are sharp velocity contrasts.
    Keywords: Marine Geosciences and Applied Geophysics
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    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 49
    Publication Date: 2014-04-15
    Description: Heterogeneity in genetic networks across different signaling molecular contexts can suggest molecular regulatory mechanisms. Here we describe a comparative chi-square analysis (CP 2 ) method, considerably more flexible and effective than other alternatives, to screen large gene expression data sets for conserved and differential interactions. CP 2 decomposes interactions across conditions to assess homogeneity and heterogeneity. Theoretically, we prove an asymptotic chi-square null distribution for the interaction heterogeneity statistic. Empirically, on synthetic yeast cell cycle data, CP 2 achieved much higher statistical power in detecting differential networks than alternative approaches. We applied CP 2 to Drosophila melanogaster wing gene expression arrays collected under normal conditions, and conditions with overexpressed E2F and Cabut, two transcription factor complexes that promote ectopic cell cycling. The resulting differential networks suggest a mechanism by which E2F and Cabut regulate distinct gene interactions, while still sharing a small core network. Thus, CP 2 is sensitive in detecting network rewiring, useful in comparing related biological systems.
    Keywords: Computational Methods, Genomics
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  • 50
    Publication Date: 2013-09-06
    Description: Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k = 8 ~10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors’ websites: e.g. http://www.cs.toronto.edu/~wkc/kmerHMM .
    Keywords: Computational Methods, Genomics
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  • 51
    Publication Date: 2014-04-15
    Description: Sequence similarity search is a fundamental way of analyzing nucleotide sequences. Despite decades of research, this is not a solved problem because there exist many similarities that are not found by current methods. Search methods are typically based on a seed-and-extend approach, which has many variants (e.g. spaced seeds, transition seeds), and it remains unclear how to optimize this approach. This study designs and tests seeding methods for inter-mammal and inter-insect genome comparison. By considering substitution patterns of real genomes, we design sets of multiple complementary transition seeds, which have better performance (sensitivity per run time) than previous seeding strategies. Often the best seed patterns have more transition positions than those used previously. We also point out that recent computer memory sizes (e.g. 60 GB) make it feasible to use multiple (e.g. eight) seeds for whole mammal genomes. Interestingly, the most sensitive settings achieve diminishing returns for human–dog and melanogaster–pseudoobscura comparisons, but not for human–mouse, which suggests that we still miss many human–mouse alignments. Our optimized heuristics find ~20 000 new human–mouse alignments that are missing from the standard UCSC alignments. We tabulate seed patterns and parameters that work well so they can be used in future research.
    Keywords: Computational Methods, Genomics
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  • 52
    Publication Date: 2014-04-15
    Description: Identifying differential features between conditions is a popular approach to understanding molecular features and their mechanisms underlying a biological process of particular interest. Although many tests for identifying differential expression of gene or gene sets have been proposed, there was limited success in developing methods for differential interactions of genes between conditions because of its computational complexity. We present a method for Evaluation of Dependency DifferentialitY (EDDY), which is a statistical test for differential dependencies of a set of genes between two conditions. Unlike previous methods focused on differential expression of individual genes or correlation changes of individual gene–gene interactions, EDDY compares two conditions by evaluating the probability distributions of dependency networks from genes. The method has been evaluated and compared with other methods through simulation studies, and application to glioblastoma multiforme data resulted in informative cancer and glioblastoma multiforme subtype-related findings. The comparison with Gene Set Enrichment Analysis, a differential expression-based method, revealed that EDDY identifies the gene sets that are complementary to those identified by Gene Set Enrichment Analysis. EDDY also showed much lower false positives than Gene Set Co-expression Analysis, a method based on correlation changes of individual gene–gene interactions, thus providing more informative results. The Java implementation of the algorithm is freely available to noncommercial users. Download from: http://biocomputing.tgen.org/software/EDDY .
    Keywords: Computational Methods, Genomics
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  • 53
    Publication Date: 2014-09-02
    Description: Inundation of evolutionary markers expedited in Human Genome Project and 1000 Genome Consortium has necessitated pruning of redundant and dependent variables. Various computational tools based on machine-learning and data-mining methods like feature selection/extraction have been proposed to escape the curse of dimensionality in large datasets. Incidentally, evolutionary studies, primarily based on sequentially evolved variations have remained un-facilitated by such advances till date. Here, we present a novel approach of recursive feature selection for hierarchical clustering of Y-chromosomal SNPs/haplogroups to select a minimal set of independent markers, sufficient to infer population structure as precisely as deduced by a larger number of evolutionary markers. To validate the applicability of our approach, we optimally designed MALDI-TOF mass spectrometry-based multiplex to accommodate independent Y-chromosomal markers in a single multiplex and genotyped two geographically distinct Indian populations. An analysis of 105 world-wide populations reflected that 15 independent variations/markers were optimal in defining population structure parameters, such as F ST , molecular variance and correlation-based relationship. A subsequent addition of randomly selected markers had a negligible effect (close to zero, i.e. 1 x 10 –3 ) on these parameters. The study proves efficient in tracing complex population structures and deriving relationships among world-wide populations in a cost-effective and expedient manner.
    Keywords: Computational Methods, Genomics
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  • 54
    Publication Date: 2014-09-17
    Description: Developing a quantitative view of how biological pathways are regulated in response to environmental factors is central for understanding of disease phenotypes. We present a computational framework, named Multivariate Inference of Pathway Activity (MIPA), which quantifies degree of activity induced in a biological pathway by computing five distinct measures from transcriptomic profiles of its member genes. Statistical significance of inferred activity is examined using multiple independent self-contained tests followed by a competitive analysis. The method incorporates a new algorithm to identify a subset of genes that may regulate the extent of activity induced in a pathway. We present an in-depth evaluation of specificity, robustness, and reproducibility of our method. We benchmarked MIPA's false positive rate at less than 1%. Using transcriptomic profiles representing distinct physiological and disease states, we illustrate applicability of our method in (i) identifying gene–gene interactions in autophagy-dependent response to Salmonella infection, (ii) uncovering gene–environment interactions in host response to bacterial and viral pathogens and (iii) identifying driver genes and processes that contribute to wound healing and response to anti-TNFα therapy. We provide relevant experimental validation that corroborates the accuracy and advantage of our method.
    Keywords: Computational Methods, Genomics
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  • 55
    Publication Date: 2014-09-17
    Description: Viral recombination is a key evolutionary mechanism, aiding escape from host immunity, contributing to changes in tropism and possibly assisting transmission across species barriers. The ability to determine whether recombination has occurred and to locate associated specific recombination junctions is thus of major importance in understanding emerging diseases and pathogenesis. This paper describes a method for determining recombinant mosaics (and their proportions) originating from two parent genomes, using high-throughput sequence data. The method involves setting the problem geometrically and the use of appropriately constrained quadratic programming. Recombinants of the honeybee deformed wing virus and the Varroa destructor virus-1 are inferred to illustrate the method from both siRNAs and reads sampling the viral genome population (cDNA library); our results are confirmed experimentally. Matlab software (MosaicSolver) is available.
    Keywords: Computational Methods, Genomics
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  • 56
    Publication Date: 2014-09-03
    Description: We report and analyse the tsunami recorded in the northwestern Indian Ocean at the Makran region following the M w 7.7 Pakistan inland strike-slip earthquake on 2013 September 24. We analyse eleven tide gauge records as well as one DART record of this tsunami and perform numerical modelling of the tsunami that would be triggered by a range of possible sources. The tsunami registered a maximum wave height of 109 cm at the Qurayat tide gauge station (Oman). The dominant period of the tsunami was around 12 min, although wavelet analysis showed that parts of the tsunami energy were partitioned into a slightly wider period range of 7 and 16 min. Tsunami backward ray tracing showed that the tsunami source was possibly located offshore Jiwani (Pakistan) and that the tsunami was most likely triggered by the main shock. The aftershocks are distributed in the inland region and the coseismic vertical and horizontal displacements are also limited inland implying that the tsunami was generated by secondary sources triggered by the earthquake. Different possible tsunami sources including a mud volcano at the location of the newly generated island, and a mud volcano or diapir at offshore deep water were examined through numerical modelling and all failed to reproduce the observed waveforms. Numerical modelling showed that a submarine slump with a source dimension of about 10–15 km and a thickness of about 100 m located at 61.49°E and 24.62°N, that is, about 60–70 km off the Jiwani coast (Pakistan), seems capable of reasonably reproducing the wave amplitudes and periods of the observed tsunami waveforms. This event was the second instrumentally recorded tsunami in the region, after the Makran tsunami of 1945 November, and provides evidence for a hazard from landslide/slump-generated waves following seismic activity in the area.
    Keywords: Marine Geosciences and Applied Geophysics
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    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 57
    Publication Date: 2014-08-07
    Description: Joint inversion of different geophysical data sets is becoming a more popular and powerful tool, and it has been performed on data sensitive both to the same physical parameter and to different physical parameters. Joint inversion is undertaken to reduce acceptable model space and to increase sensitivity to model parameters that one method alone is unable to resolve adequately. We examine and implement a novel hybrid joint inversion approach. In our inversion scheme a model—the reference model—is fixed, and the information shared with the subsurface structure obtained from another method will be maximized; in our case conductivity structures from magnetotelluric (MT) inversion. During inversion, the joint probability distribution of the MT and the specified reference model is estimated and its entropy minimized in order to guide the inversion result towards a solution that is statistically compatible with the reference model. The powerful feature of this technique is that no explicit relationships between estimated model parameters and reference model ones are presumed: if a link exists in data then it is highlighted in the estimation of the joint probability distribution, if no link is required, then none is enforced. Tests performed verify the robustness of this method and the advantages of it in a 1-D anisotropic scenario are demonstrated. A case study was performed with data from Central Germany, effectively fitting an MT data set from a single station within as minimal an amount of anisotropy as required.
    Keywords: Marine Geosciences and Applied Geophysics
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    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 58
    Publication Date: 2014-08-14
    Description: Several slope failures are observed near the deformation front on the frontal ridges of the northern Cascadia accretionary margin off Vancouver Island. The cause for these events is not clear, although several lines of evidence indicate a possible connection between the occurrence of gas hydrate and submarine landslide features. The presence of gas hydrate is indicated by a prominent bottom-simulating reflector (BSR), at a depth of ~265–275 m beneath the seafloor (mbsf), as interpreted from vertical-incidence and wide-angle seismic data beneath the ridge crests of the frontal ridges. For one slide, informally called Slipstream Slide, the velocity structure inferred from tomography analyses shows anomalous high velocities values of about 2.0 km s –1 at shallow depths of 100 mbsf. The estimated depth of the glide plane (100 ± 10 m) closely matches the depth of these shallow high velocities. In contrast, at a frontal ridge slide just to the northwest (informally called Orca Slide), the glide plane occurs at the same depth as the current BSR. Our new results indicate that the glide plane of the Slipstream slope failure is associated with the contrast between sediments strengthened by gas hydrate and overlying sediments where little or no hydrate is present. In contrast, the glide plane of Orca Slide is between sediment strengthened by hydrate underlain by sediments beneath the gas hydrate stability zone, possibly containing free gas. Additionally, a set of margin perpendicular normal faults are imaged from seafloor down to BSR depth at both frontal ridges. As inferred from the multibeam bathymetry, the estimated volume of the material lost during the slope failure at Slipstream Slide is about 0.33 km 3 , and ~0.24 km 3 of this volume is present as debris material on the ocean basin floor. The 20 per cent difference is likely due to more widely distributed fine sediments not easily detectable as bathymetric anomalies. These volume estimates on the Cascadia margin are approaching the mass failure volume for other slides that have generated large tsunamis—for example 1–3 km 3 for a 1998 Papua New Guinea slide.
    Keywords: Marine Geosciences and Applied Geophysics
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    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 59
    Publication Date: 2014-08-14
    Description: The method presented here aims to assess the tsunami threat very rapidly after the occurrence of a large earthquake, using as input the parameters of the seismic source, and an approach based on Green's summation. We show that the main weakness of the approach (the need to consider only linear shallow water propagation) is largely compensated by the advantages in terms of computing performance and independence with respect to pre-computed scenarios. To test the approach and to illustrate its implementation in a real environment, we focus on the Sea of Oman, a tsunamigenic area characterized by Makran subduction zone which detailed structure is partially unknown and where secondary tsunami sources must also be taken into account, both for hazard studies and warning purposes. The potential source area is partitioned into a grid of unity water sources. A shallow water (SW) numerical model is used to pre-compute the corresponding empirical Green's functions on several points of interest located on the coasts of Iran, Pakistan and Oman. The comparison between Green's summation and the direct SW computation using the full resolution of the bathymetric grid shows that the accuracy is good enough for practical applications.
    Keywords: Marine Geosciences and Applied Geophysics
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    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 60
    Publication Date: 2014-08-18
    Description: Clay minerals as products of hydrothermal alteration significantly influence the hydraulic and mechanical properties of crystalline rock. Therefore, the localization and characterization of alteration zones by downhole measurements is a great challenge for the development of geothermal reservoirs. The magnetite bearing granite of the geothermal site in Soultz-sous-Forêts (France) experienced hydrothermal alteration during several tectonic events and clay mineral formation is especially observed in alteration halos around fracture zones. During the formation of clay minerals, magnetite was oxidized into hematite, which significantly reduces the magnetic susceptibility of the granite from ferrimagnetic to mostly paramagnetic values. The aim of this study was to find out if there exists a correlation between synthetic clay content logs (SCCLs) and measurements of magnetic susceptibility on cuttings in the granite in order to characterize their alteration mineralogy. Such a correlation has been proven for core samples of the EPS1 reference well. SCCLs were created from gamma ray and fracture density logs using a neural network. These logs can localize altered fracture zones in the GPK1-4 wells, where no core material is available. Mass susceptibility from 261 cutting samples of the wells GPK1–GPK4 was compared with the neural network derived synthetic logs. We applied a combination of temperature dependent magnetic susceptibility measurements with optical and electron microscopy, and energy dispersive X-ray spectroscopy to discriminate different stages of alteration. We found, that also in the granite cuttings an increasing alteration grade is characterized by an advancing oxidation of magnetite into hematite and a reduction of magnetic susceptibility. A challenge to face for the interpretation of magnetic susceptibility data from cuttings material is that extreme alteration grades can also display increased susceptibilities due to the formation of secondary magnetite. Low magnetic susceptibility can also be attributed to primary low magnetite content, if the granite facies changes. In order to interpret magnetic susceptibility from cuttings, contaminations with iron from wear debris of the drilling tools must be eliminated. Provided that the magnetic mineralogy of the granite is known in detail, this method in combination with petrographic investigations is suited to indicate and characterize hydrothermal alteration and the appearance of clay.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 61
    Publication Date: 2014-08-13
    Description: Elastic and mechanical weakening from water saturation are widely known to occur in sedimentary rocks, and particularly in carbonate rocks. To improve our understanding of the physics underlying this phenomenon, ultrasonic ( f  ~ 0.5 MHz) elastic properties are measured on a large suite of clean limestones and sandstones at very low saturations from relative humidity (RH) variations at ambient conditions. Measurements clearly highlight an elastic weakening (i.e. decrease in elastic wave velocity) from moisture adsorption. P - and S -wave velocities are similarly affected by adsorption, but in a different way for limestones and sandstone samples. While the elastic properties of limestone samples show almost no RH dependence, a large weakening is observed for samples of Fontainebleau sandstone that increases with the samples’ porosity. The main elastic weakening effect is likely to result from adsorption of fluid at grain contacts. It thus affects particularly granular rocks such as sandstones while well-cemented limestones are not affected. The granular model from Murphy et al. , accounting for surface energy effects, proves to be appropriate. Applying this model, it is shown that (i) P - and S -wave velocities have the same dependence on surface energy, which is consistent with the measurements and (ii) surface energy values obtained from the ultrasonic data using this model correlate with RH, and are consistent with the expected value for quartz crystals at vapour pressure. Yet, porosity, which relates to degree of cementation in the particular case of Fontainebleau sandstone, appears to be an additional parameter. A modified model is thus derived using the cementation model from Digby, accounting for a bonding radius at grain contact. It proves to apply well to the measured data. The fundamental difference between limestones’ and sandstones’ dependence to RH appears to be related to a microstructural difference. Saturation variations from RH increase depend on specific surface area, which is particularly low in Fontainebleau sandstones and large in microporous limestones. However elastic weakening from RH is more important in sandstones owing to their granular microstructure.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 62
    Publication Date: 2014-07-20
    Description: A novel experimental method is introduced to estimate the Thomsen's elastic anisotropy parameters and of a transversely isotropic shale under variable stress and saturation conditions. The method consists in recording P -wave velocities along numerous paths on a cylindrical specimen using miniature ultrasonic transducers. Such an overdetermined set of measurements is specifically designed to reduce the uncertainty associated with the determination of Thomsen's parameter compared to the classical method for which a single off-axis measurement is used (usually at 45° to the specimen's axis). This method is applied to a specimen of Opalinus Clay recovered from the Mont-Terri Underground Research Laboratory in Switzerland. The specimen is first saturated with brine at low effective pressure and then subjected to an effective pressure cycle up to 40 MPa, followed by a triaxial loading up to failure. During saturation and deformation, the evolution of P -wave velocities along a maximum of 240 ray paths is monitored and Thomsen's parameters α , and are computed by fitting Thomsen's weak anisotropy model to the data. The values of and obtained at the highest confining pressures reached during the experiment are comparable with those predicted from X-ray diffraction texture analysis and modelling for Opalinus Clay reported in the literature. These models neglect the effect of soft-porosity on elastic properties, but become relevant when soft porosity is closed at high effective pressure.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 63
    Publication Date: 2014-08-03
    Description: We present a novel accurate and efficient goal-oriented adaptive finite-element method solution for complex multi-electrodes resistivity system with arbitrary smooth surface topographies. A simple Green's function of a half-space model is adopted to eliminate the singularity. A unified boundary value problem for the regular potential is formulated for a multi-electrodes system so that it shares a common system matrix. In addition, a goal-oriented error estimation technique is developed to generate an optimal common grid so that highly accurate solutions are obtained with minimum computation cost. Synthetic models are used to verify our algorithm and excellent agreements are obtained by comparing with other methods.
    Keywords: Marine Geosciences and Applied Geophysics
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  • 64
    Publication Date: 2013-06-08
    Description: An appreciable fraction of introns is thought to have some function, but there is no obvious way to predict which specific intron is likely to be functional. We hypothesize that functional introns experience a different selection regime than non-functional ones and will therefore show distinct evolutionary histories. In particular, we expect functional introns to be more resistant to loss, and that this would be reflected in high conservation of their position with respect to the coding sequence. To test this hypothesis, we focused on introns whose function comes about from microRNAs and snoRNAs that are embedded within their sequence. We built a data set of orthologous genes across 28 eukaryotic species, reconstructed the evolutionary histories of their introns and compared functional introns with the rest of the introns. We found that, indeed, the position of microRNA- and snoRNA-bearing introns is significantly more conserved. In addition, we found that both families of RNA genes settled within introns early during metazoan evolution. We identified several easily computable intronic properties that can be used to detect functional introns in general, thereby suggesting a new strategy to pinpoint non-coding cellular functions.
    Keywords: Computational Methods, Genomics
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  • 65
    Publication Date: 2012-06-28
    Description: Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory ‘grammar’, or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila .
    Keywords: Computational Methods, Genomics
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  • 66
    Publication Date: 2012-08-23
    Description: The field of regulatory genomics today is characterized by the generation of high-throughput data sets that capture genome-wide transcription factor (TF) binding, histone modifications, or DNAseI hypersensitive regions across many cell types and conditions. In this context, a critical question is how to make optimal use of these publicly available datasets when studying transcriptional regulation. Here, we address this question in Drosophila melanogaster for which a large number of high-throughput regulatory datasets are available. We developed i-cisTarget (where the ‘ i ’ stands for integrative ), for the first time enabling the discovery of different types of enriched ‘regulatory features’ in a set of co-regulated sequences in one analysis, being either TF motifs or ‘ in vivo ’ chromatin features, or combinations thereof. We have validated our approach on 15 co-expressed gene sets, 21 ChIP data sets, 628 curated gene sets and multiple individual case studies, and show that meaningful regulatory features can be confidently discovered; that bona fide enhancers can be identified, both by in vivo events and by TF motifs; and that combinations of in vivo events and TF motifs further increase the performance of enhancer prediction.
    Keywords: Computational Methods, Genomics
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  • 67
    Publication Date: 2013-11-21
    Description: Traditional methods that aim to identify biomarkers that distinguish between two groups, like Significance Analysis of Microarrays or the t -test, perform optimally when such biomarkers show homogeneous behavior within each group and differential behavior between the groups. However, in many applications, this is not the case. Instead, a subgroup of samples in one group shows differential behavior with respect to all other samples. To successfully detect markers showing such imbalanced patterns of differential signal, a different approach is required. We propose a novel method, specifically designed for the Detection of Imbalanced Differential Signal (DIDS). We use an artificial dataset and a human breast cancer dataset to measure its performance and compare it with three traditional methods and four approaches that take imbalanced signal into account. Supported by extensive experimental results, we show that DIDS outperforms all other approaches in terms of power and positive predictive value. In a mouse breast cancer dataset, DIDS is the only approach that detects a functionally validated marker of chemotherapy resistance. DIDS can be applied to any continuous value data, including gene expression data, and in any context where imbalanced differential signal is manifested.
    Keywords: Computational Methods, Genomics
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  • 68
    Publication Date: 2013-11-22
    Description: Following the failure of legislative proposals for a multi-sector greenhouse gas (GHG) cap-and-trade policy, the shift in focus to energy sector policies ignores the perhaps substantial potential for GHG mitigation from agriculture/forestry. We review estimates of the current U.S. agriculture sector contribution to GHG mitigation from a portfolio of existing sector policies in bioenergy, conservation, and research and development to compare accomplishments across programs. We then consider what opportunities and challenges may exist for increasing sector GHG mitigation by retargeting and/or expanding current programs—or for bioenergy-related mitigation, implementing proposed new programs—to serve as an alternative to cap-and-trade.
    Keywords: Q16 - R&D ; Agricultural Technology ; Agricultural Extension Services, Q42 - Alternative Energy Sources, Q54 - Climate ; Natural Disasters ; Global Warming, Q58 - Government Policy
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 69
    Publication Date: 2013-11-22
    Description: This paper explores federal policies, other than a carbon price, for reducing emissions from the electric power sector. These policies fall into two major categories: policies that encourage the development of non- or low-emitting energy sources, and regulatory policies under existing legal authority (primarily the Clean Air Act). The paper provides an overview of policy options and a few concrete proposals, along with a summary of insights from economists on their advantages and disadvantages. Economists generally disfavor investment subsidies, but comparing other policy options, including regulatory approaches, technology mandates, and production subsidies, is complex. Excluding existing clean generation from incentive policies is tempting but can lead to perverse outcomes.
    Keywords: L94 - Electric Utilities, Q54 - Climate ; Natural Disasters ; Global Warming
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 70
    Publication Date: 2014-06-22
    Description: The Geological Survey of Sweden has been collecting airborne tensor very low frequency data (VLF) over several decades, covering large parts of the country. The data has been an invaluable source of information for identifying conductive structures that can among other things be related to water-filled fault zones, wet sediments that fill valleys or ore mineralizations. Because the method only uses two differently polarized plane waves of very similar frequency, vertical resolution is low and interpretation is in most cases limited to maps that are directly derived from the data. Occasionally, 2-D inversion is carried out along selected profiles. In this paper, we present for the first time a 3-D inversion for tensor VLF data in order to further increase the usefulness of the data set. The inversion is performed using a non-linear conjugate gradient scheme (Polak-Ribière) with an inexact line-search. The gradient is obtained by an algebraic adjoint method that requires one additional forward calculation involving the adjoint system matrix. The forward modelling is based on integral equations with an analytic formulation of the half-space Green's tensor. It avoids typically required Hankel transforms and is particularly amenable to singularity removal prior to the numerical integration over the volume elements. The system is solved iteratively, thus avoiding construction and storage of the dense system matrix. By using fast 3-D Fourier transforms on nested grids, subsequently farther away interactions are represented with less detail and therefore with less computational effort, enabling us to bridge the gap between the relatively short wavelengths of the fields (tens of metres) and the large model dimensions (several square kilometres). We find that the approximation of the fields can be off by several per cent, yet the transfer functions in the air are practically unaffected. We verify our code using synthetic calculations from well-established 2-D methods, and trade modelling accuracy off against computational effort in order to keep the inversion feasible in both respects. Our compromise is to limit the permissible resistivity to not fall below 100 m to maintain computational domains as large as 10 10 km 2 and computation times on the order of a few hours on standard PCs. We investigate the effect of possible local violations of these limits. Even though the conductivity magnitude can then not be recovered correctly, we do not observe any structural artefacts related to this in our tests. We invert a data set from northern Sweden, where we find an excellent agreement of known geological features, such as contacts or fault zones, with elongated conductive structures, while high resistivity is encountered in probably less disturbed geology, often related to topographic highs, which have survived predominantly glacial erosion processes. As expected from synthetic studies, the resolution is laterally high, but vertically limited down to the top of conductive structures.
    Keywords: Marine Geosciences and Applied Geophysics
    Print ISSN: 0956-540X
    Electronic ISSN: 1365-246X
    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 71
    Publication Date: 2014-06-28
    Description: Induced polarization is a geophysical method looking to image and interpret low-frequency polarization mechanisms occurring in porous media. Below 10 kHz, the quadrature conductivity of metal-free sandy and clayey materials exhibits a distribution of relaxation times, which can be related to the pore size distribution of these porous materials. When the polarization spectra are fitted with a Cole–Cole model, we first observe that the main relaxation time is controlled by the main pore size of the material and that the Cole–Cole exponent c is never much above 0.5, a value corresponding to a Warburg function. The complex conductivity is then obtained through a convolution product between the pore size distribution and such Warburg function. We also provide a way to recover the pore size distribution by performing a deconvolution of measured spectra using the Warburg function. A new dataset of mercury porosimetry and induced polarization data of six siliciclastic materials supports the hypothesis that the Cole–Cole relaxation time is strongly controlled by the pore size, and especially the characteristic pore size corresponding to the peak of the pore size distribution from mercury porosimetry. The distribution of the pore throat sizes of these materials seems fairly well recovered using the Warburg decomposition of the spectral induced polarization spectra but additional data will be needed to confirm this finding.
    Keywords: Marine Geosciences and Applied Geophysics
    Print ISSN: 0956-540X
    Electronic ISSN: 1365-246X
    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 72
    Publication Date: 2014-06-28
    Description: We propose a new, simple and efficient method to image electrical resistivity between a set of wells. Our procedure consists of two steps: first, we map the interfaces between various subsurface formations using seismoelectric conversions; second, we derive the formation resistivity using image-guided cross-well electric tomography. In the first step, we focus seismic energy at a set of points located on a regular grid between wells, which enables us to map the geological formations in terms of heterogeneities in electrical, hydraulic and/or seismic properties. The density of the scanning points (i.e. the seismoelectric image resolution) is related to the wavelength of the seismic impulse used to scan the formations. Each time the seismic energy is focused at a point, the resulting electrical potential burst (equivalent to the one generated by a volumetric seismic source) is recorded remotely at a set of electrodes positioned in wells (the reference electrode can be located on the ground surface or far enough to be considered at infinity). We construct a high-resolution ‘seismoelectric’ image by assigning the electrical potential simulated at these fixed electrodes to the location of the seismic focus. In a follow-up step, the structure of this image is used in image-guided inversion to improve electrical resistivity tomography between the two wells. The structural information from the seismoelectric image is used to impose constraints on the model covariance matrix used in the inversion of the electrical resistivity data. This approach offers new perspectives in recovering fine structure of resistivity (high definition resistivity tomography) between the wells, which cannot be resolved through conventional cross-well resistivity or from seismic tomography alone.
    Keywords: Marine Geosciences and Applied Geophysics
    Print ISSN: 0956-540X
    Electronic ISSN: 1365-246X
    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 73
    Publication Date: 2014-03-07
    Description: Within the European Union, it is agreed that watershed-based management of water quality problems is more efficient than centralised arrangements. In this study, a mechanism for allocating international funds to watershed authorities for nitrogen abatement in the presence of moral hazard is investigated. The results show that when there is a risk of climate change, the cost of moral hazard to the international funding agency can be high if there is a moderate likelihood of climate change and the watershed authority is guaranteed a high minimum compensation.
    Keywords: Q53 - Air Pollution ; Water Pollution ; Noise ; Hazardous Waste ; Solid Waste ; Recycling, Q54 - Climate ; Natural Disasters ; Global Warming, Q58 - Government Policy
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 74
    Publication Date: 2014-07-23
    Description: In the United States, climate change is likely to increase average daily temperatures and the frequency of heat waves, which can reduce meat and milk production in animals. Methods that livestock producers use to mitigate thermal stress—including modifications to animal management or housing—tend to increase production costs. We use operation-level economic data coupled with finely-scaled climate data to estimate how the local thermal environment affects the technical efficiency of dairies across the United States. We then use this information to estimate the possible decline in milk production in 2030 resulting from climate change-induced heat stress under the simplifying assumptions that the production technology, location of production, and other factors are held constant. For four climate model scenarios, the results indicate modest heat-stress-related production declines by 2030, with the largest declines occurring in the southern states.
    Keywords: D24 - Production ; Cost ; Capital and Total Factor Productivity ; Capacity, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q54 - Climate ; Natural Disasters ; Global Warming
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 75
    Publication Date: 2014-07-23
    Description: A growing body of evidence shows a causal relationship between extreme weather events and civil conflict incidence at the global level. We find that this causality is also valid for droughts and local violent conflicts in a within-country setting over a short time frame in the case of Somalia. We estimate that a one standard deviation increase in drought intensity and length raises the likelihood of conflict by 62%. We also find that drought affects conflict through livestock price changes, establishing livestock markets as the primary channel of transmission in Somalia.
    Keywords: D74 - Conflict ; Conflict Resolution ; Alliances, O12 - Microeconomic Analyses of Economic Development, Q11 - Aggregate Supply and Demand Analysis ; Prices, Q54 - Climate ; Natural Disasters ; Global Warming
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 76
    Publication Date: 2014-07-23
    Description: Due to the failure of international efforts to limit atmospheric concentrations of greenhouse gases, consideration is now being given to solar geoengineering—a deliberate intervention to limit global warming without altering the atmospheric concentration of greenhouse gases. In contrast to emission cuts, geoengineering is expected to be cheap, quick to lower temperature, and feasible through the use of a single intervention. However, geoengineering is an imperfect substitute for emission reductions and will likely have undesirable side effects, only some of which can be anticipated before geoengineering is deployed. Most importantly, because geoengineering can be undertaken unilaterally, it creates issues of governance: Who gets to decide if, when, and how geoengineering should be attempted? This article provides an introduction to the key issues surrounding the governance of this unprecedented technology. ( JEL : Q54, F53, K33)
    Keywords: Q54 - Climate ; Natural Disasters ; Global Warming, F53 - International Agreements and Observance ; International Organizations, K33 - International Law
    Print ISSN: 1750-6816
    Electronic ISSN: 1750-6824
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Political Science , Economics
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  • 77
    Publication Date: 2014-07-23
    Description: Climate engineering measures are designed to either reduce atmospheric carbon concentration (by growing trees or spreading iron in the ocean, for example) or directly influence the radiation reaching or leaving the earth (by injecting sulfur into the stratosphere or modifying cloud formations, for example) to compensate for greenhouse gas–induced warming. The former measures are termed carbon dioxide removal (CDR), which we characterize as a low-leverage causative approach, and the latter are termed radiation management (RM), which we characterize as a high-leverage symptomatic approach. There are similarities between CDR and emission control. Accordingly, benefit-cost analysis can be used to assess certain CDR measures. By contrast, high-leverage RM represents a genuinely new option in the climate change response portfolio, at first glance promising insurance against fat-tail climate change risks. However, the persistent intrinsic uncertainties of RM suggest that any cautious climate risk management approach should consider RM as a complement to (rather than a substitute for) emission control at best. Moreover, the complexity of the earth system imposes major limitations on the ability of research to reduce these uncertainties. Thus we argue that a research strategy is needed that focuses on increasing our basic understanding of the earth system and conducting comprehensive assessments of the risk(s) associated with both climate change and the deployment of climate engineering. ( JEL : Q52, Q54, Q55)
    Keywords: Q52 - Pollution Control Costs ; Distributional Effects ; Employment Effects, Q54 - Climate ; Natural Disasters ; Global Warming, Q55 - Technological Innovation
    Print ISSN: 1750-6816
    Electronic ISSN: 1750-6824
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Political Science , Economics
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  • 78
    Publication Date: 2014-07-23
    Description: Climate scientists, and natural scientists more generally, believe that climate change is a major, perhaps the most important, problem facing humankind this century, and that it is increasingly linked to extreme weather events. However, the impression one gets from much of the economic literature, particularly simulations from integrated assessment models used in policy analysis, is that the potential impacts of climate change are not large enough to warrant aggressive mitigation efforts in the near term. Although these models represent an important step in the needed interdisciplinary analysis of climate change by elucidating the links between climate and economy, we argue that they grossly underestimate potential impacts and associated damages because they (and the related policy analyses) fail to adequately capture extreme conditions, catastrophic events, and tipping points that trigger irreversible changes in the climate system, as well as impacts on the natural environment that cannot be monetized. Because the most severe impacts are expected in the later years of this century and beyond, discounting is crucial, and we argue that the appropriate rate is well below market rates. Moreover, we show that in the uniquely long period relevant to climate policy, the irreversibility of climate changes and impacts is more serious than the irreversibility of proposed mitigation measures. We conclude that an aggressive mitigation policy is warranted, one that holds further increases in global mean temperature to the scientific consensus on what is required to avoid the worst impacts, and that such a policy can be achieved at a cost that is well below potential damages. ( JEL : Q54)
    Keywords: Q54 - Climate ; Natural Disasters ; Global Warming
    Print ISSN: 1750-6816
    Electronic ISSN: 1750-6824
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Political Science , Economics
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  • 79
    Publication Date: 2014-07-29
    Description: In subduction zones, shallow subsurface structures are the manifestation of the plate interactions at depth. However, significant water depths, rough bathymetry and presence of heavily deformed accretionary wedge materials hamper imaging of the near-surface features to a great extent using conventional imaging techniques. In this study, we show results using an integrated processing technique to a multichannel seismic data set acquired in 2006 from the northwestern offshore Sumatra. We start with first downward continuing the 12-km-long surface streamer data to the seafloor, followed by a high-resolution traveltime tomography of refracted phases to determine a detailed velocity–depth model of subsurface, which in turns, is used for pre-stack depth migration in order to delineate the shallow subsurface structures beneath the trench, subduction front and outer accretionary wedge. Our velocity–depth model and the depth migrated image depict variation of sediment properties across the front and structures of uppermost sedimentary sequence with an unprecedented high resolution providing the precise location of the frontal and conjugate thrusts, highly folded sedimentary sequences, which in turns describe their relationship with the top of the subducting plate and factors that control rupture propagation to the trench. Furthermore, we estimate the porosity distribution across the front, where we find a 12 and 18 per cent decrease in porosity beneath the deformation front and the inner accretionary plateau at 500 m below the seafloor, respectively, which we interpret to be due to the compaction. A significant decrease in porosity at the plate interface below 5–6-km thick sediments near the deformation front would increase the coupling, leading to the rupture propagation up to the trench, uplifting 4.5 km water and producing large tsunami.
    Keywords: Marine Geosciences and Applied Geophysics
    Print ISSN: 0956-540X
    Electronic ISSN: 1365-246X
    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 80
    Publication Date: 2014-08-01
    Description: Gene set enrichment testing can enhance the biological interpretation of ChIP-seq data. Here, we develop a method, ChIP-Enrich, for this analysis which empirically adjusts for gene locus length (the length of the gene body and its surrounding non-coding sequence). Adjustment for gene locus length is necessary because it is often positively associated with the presence of one or more peaks and because many biologically defined gene sets have an excess of genes with longer or shorter gene locus lengths. Unlike alternative methods, ChIP-Enrich can account for the wide range of gene locus length-to-peak presence relationships (observed in ENCODE ChIP-seq data sets). We show that ChIP-Enrich has a well-calibrated type I error rate using permuted ENCODE ChIP-seq data sets; in contrast, two commonly used gene set enrichment methods, Fisher's exact test and the binomial test implemented in Genomic Regions Enrichment of Annotations Tool (GREAT), can have highly inflated type I error rates and biases in ranking. We identify DNA-binding proteins, including CTCF, JunD and glucocorticoid receptor α (GRα), that show different enrichment patterns for peaks closer to versus further from transcription start sites. We also identify known and potential new biological functions of GRα. ChIP-Enrich is available as a web interface ( http://chip-enrich.med.umich.edu ) and Bioconductor package.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 81
    Publication Date: 2014-06-30
    Description: We present a scale- and parameter-adaptive method to pre-condition the gradient of the parameters to be inverted in time-domain 2-D elastic full-waveform inversion (FWI). The proposed technique, which relies on a change of variables of the model parameters, allows to balance the value of the gradient of the Lamé parameters and density throughout the model in each step of the multiscale inversion. The main difference compared to existing gradient pre-conditioners is that the variables are automatically selected based on a least-squares minimization criteria of the gradient weight, which corresponds to the product of the gradient by a power of the parameter to be inverted. Based on numerical tests made with (1) a modified version of the Marmousi-2 model, and (2) a high-velocity and density local anomaly model, we illustrate that the value of the power helps to balance the gradient throughout the model. In addition, we show that a particular value exists for each parameter that optimizes the inversion results in terms of accuracy and efficiency. For the two models, the optimal power is ~2.0–2.5 and ~1.5 for the first and second Lamé parameters, respectively; and between 3 and 6, depending on the inverted frequency, for density. These power values provide the fastest and most accurate inversion results for the three parameters in the framework of multiscale and multishooting FWI using three different optimization schemes.
    Keywords: Marine Geosciences and Applied Geophysics
    Print ISSN: 0956-540X
    Electronic ISSN: 1365-246X
    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 82
    Publication Date: 2013-01-20
    Description: Identification of differentially expressed subnetworks from protein–protein interaction (PPI) networks has become increasingly important to our global understanding of the molecular mechanisms that drive cancer. Several methods have been proposed for PPI subnetwork identification, but the dependency among network member genes is not explicitly considered, leaving many important hub genes largely unidentified. We present a new method, based on a bagging Markov random field (BMRF) framework, to improve subnetwork identification for mechanistic studies of breast cancer. The method follows a maximum a posteriori principle to form a novel network score that explicitly considers pairwise gene interactions in PPI networks, and it searches for subnetworks with maximal network scores. To improve their robustness across data sets, a bagging scheme based on bootstrapping samples is implemented to statistically select high confidence subnetworks. We first compared the BMRF-based method with existing methods on simulation data to demonstrate its improved performance. We then applied our method to breast cancer data to identify PPI subnetworks associated with breast cancer progression and/or tamoxifen resistance. The experimental results show that not only an improved prediction performance can be achieved by the BMRF approach when tested on independent data sets, but biologically meaningful subnetworks can also be revealed that are relevant to breast cancer and tamoxifen resistance.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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  • 83
    Publication Date: 2013-01-20
    Description: miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing new strategies to identify precursor miRNAs. miRDeep* has a user-friendly graphic interface and accepts raw data in FastQ and Sequence Alignment Map (SAM) or the binary equivalent (BAM) format. Known and novel miRNA expression levels, as measured by the number of reads, are displayed in an interface, which shows each RNAseq read relative to the pre-miRNA hairpin. The secondary pre-miRNA structure and read locations for each predicted miRNA are shown and kept in a separate figure file. Moreover, the target genes of known and novel miRNAs are predicted using the TargetScan algorithm, and the targets are ranked according to the confidence score. miRDeep* is an integrated standalone application where sequence alignment, pre-miRNA secondary structure calculation and graphical display are purely Java coded. This application tool can be executed using a normal personal computer with 1.5 GB of memory. Further, we show that miRDeep* outperformed existing miRNA prediction tools using our LNCaP and other small RNAseq datasets. miRDeep* is freely available online at http://www.australianprostatecentre.org/research/software/mirdeep-star .
    Keywords: Computational Methods, Genomics
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  • 84
    Publication Date: 2013-01-20
    Description: The mRNA export complex TREX (TREX) is known to contain Aly, UAP56, Tex1 and the THO complex, among which UAP56 is required for TREX assembly. Here, we systematically investigated the role of each human TREX component in TREX assembly and its association with the mRNA. We found that Tex1 is essentially a subunit of the THO complex. Aly, THO and UAP56 are all required for assembly of TREX, in which Aly directly interacts with THO subunits Thoc2 and Thoc5. Both Aly and THO function in linking UAP56 to the cap-binding protein CBP80. Interestingly, association of UAP56 with the spliced mRNA, but not with the pre-mRNA, requires Aly and THO. Unexpectedly, we found that Aly and THO require each other to associate with the spliced mRNA. Consistent with these biochemical results, similar to Aly and UAP56, THO plays critical roles in mRNA export. Together, we propose that Aly, THO and UAP56 form a highly integrated unit to associate with the spliced mRNA and function in mRNA export.
    Keywords: Computational Methods, Genomics
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  • 85
    Publication Date: 2012-09-27
    Description: Due to advances in high-throughput biotechnologies biological information is being collected in databases at an amazing rate, requiring novel computational approaches that process collected data into new knowledge in a timely manner. In this study, we propose a computational framework for discovering modular structure, relationships and regularities in complex data. The framework utilizes a semantic-preserving vocabulary to convert records of biological annotations of an object, such as an organism, gene, chemical or sequence, into networks (Anets) of the associated annotations. An association between a pair of annotations in an Anet is determined by the similarity of their co-occurrence pattern with all other annotations in the data. This feature captures associations between annotations that do not necessarily co-occur with each other and facilitates discovery of the most significant relationships in the collected data through clustering and visualization of the Anet. To demonstrate this approach, we applied the framework to the analysis of metadata from the Genomes OnLine Database and produced a biological map of sequenced prokaryotic organisms with three major clusters of metadata that represent pathogens, environmental isolates and plant symbionts.
    Keywords: Computational Methods, Genomics
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  • 86
    Publication Date: 2012-09-27
    Description: We describe here a novel method for integrating gene and miRNA expression profiles in cancer using feed-forward loops (FFLs) consisting of transcription factors (TFs), miRNAs and their common target genes. The dChip-GemiNI (Gene and miRNA Network-based Integration) method statistically ranks computationally predicted FFLs by their explanatory power to account for differential gene and miRNA expression between two biological conditions such as normal and cancer. GemiNI integrates not only gene and miRNA expression data but also computationally derived information about TF–target gene and miRNA–mRNA interactions. Literature validation shows that the integrated modeling of expression data and FFLs better identifies cancer-related TFs and miRNAs compared to existing approaches. We have utilized GemiNI for analyzing six data sets of solid cancers (liver, kidney, prostate, lung and germ cell) and found that top-ranked FFLs account for ~20% of transcriptome changes between normal and cancer. We have identified common FFL regulators across multiple cancer types, such as known FFLs consisting of MYC and miR-15/miR-17 families, and novel FFLs consisting of ARNT, CREB1 and their miRNA partners. The results and analysis web server are available at http://www.canevolve.org/dChip-GemiNi .
    Keywords: Computational Methods, Genomics
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  • 87
    Publication Date: 2012-10-24
    Description: Recent technology has made it possible to simultaneously perform multi-platform genomic profiling (e.g. DNA methylation (DM) and gene expression (GE)) of biological samples, resulting in so-called ‘multi-dimensional genomic data’. Such data provide unique opportunities to study the coordination between regulatory mechanisms on multiple levels. However, integrative analysis of multi-dimensional genomics data for the discovery of combinatorial patterns is currently lacking. Here, we adopt a joint matrix factorization technique to address this challenge. This method projects multiple types of genomic data onto a common coordinate system, in which heterogeneous variables weighted highly in the same projected direction form a multi-dimensional module (md-module). Genomic variables in such modules are characterized by significant correlations and likely functional associations. We applied this method to the DM, GE, and microRNA expression data of 385 ovarian cancer samples from the The Cancer Genome Atlas project. These md-modules revealed perturbed pathways that would have been overlooked with only a single type of data, uncovered associations between different layers of cellular activities and allowed the identification of clinically distinct patient subgroups. Our study provides an useful protocol for uncovering hidden patterns and their biological implications in multi-dimensional ‘omic’ data.
    Keywords: Computational Methods, Genomics
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  • 88
    Publication Date: 2012-10-24
    Description: Tandem repeats occur frequently in biological sequences. They are important for studying genome evolution and human disease. A number of methods have been designed to detect a single tandem repeat in a sliding window. In this article, we focus on the case that an unknown number of tandem repeat segments of the same pattern are dispersively distributed in a sequence. We construct a probabilistic generative model for the tandem repeats, where the sequence pattern is represented by a motif matrix. A Bayesian approach is adopted to compute this model. Markov chain Monte Carlo (MCMC) algorithms are used to explore the posterior distribution as an effort to infer both the motif matrix of tandem repeats and the location of repeat segments. Reversible jump Markov chain Monte Carlo (RJMCMC) algorithms are used to address the transdimensional model selection problem raised by the variable number of repeat segments. Experiments on both synthetic data and real data show that this new approach is powerful in detecting dispersed short tandem repeats. As far as we know, it is the first work to adopt RJMCMC algorithms in the detection of tandem repeats.
    Keywords: Computational Methods, Genomics
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  • 89
    Publication Date: 2012-11-04
    Description: Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein–protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at http://www.babelomics.org ) based on HTML5 technologies is also provided to run the algorithm and represent the network.
    Keywords: Computational Methods, Genomics
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  • 90
    Publication Date: 2012-11-04
    Description: An important step in ‘metagenomics’ analysis is the assembly of multiple genomes from mixed sequence reads of multiple species in a microbial community. Most conventional pipelines use a single-genome assembler with carefully optimized parameters. A limitation of a single-genome assembler for de novo metagenome assembly is that sequences of highly abundant species are likely misidentified as repeats in a single genome, resulting in a number of small fragmented scaffolds. We extended a single-genome assembler for short reads, known as ‘Velvet’, to metagenome assembly, which we called ‘MetaVelvet’, for mixed short reads of multiple species. Our fundamental concept was to first decompose a de Bruijn graph constructed from mixed short reads into individual sub-graphs, and second, to build scaffolds based on each decomposed de Bruijn sub-graph as an isolate species genome. We made use of two features, the coverage (abundance) difference and graph connectivity, for the decomposition of the de Bruijn graph. For simulated datasets, MetaVelvet succeeded in generating significantly higher N50 scores than any single-genome assemblers. MetaVelvet also reconstructed relatively low-coverage genome sequences as scaffolds. On real datasets of human gut microbial read data, MetaVelvet produced longer scaffolds and increased the number of predicted genes.
    Keywords: Computational Methods, Genomics
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  • 91
    Publication Date: 2012-11-04
    Description: Tandem repeats (TRs) represent one of the most prevalent features of genomic sequences. Due to their abundance and functional significance, a plethora of detection tools has been devised over the last two decades. Despite the longstanding interest, TR detection is still not resolved. Our large-scale tests reveal that current detectors produce different, often nonoverlapping inferences, reflecting characteristics of the underlying algorithms rather than the true distribution of TRs in genomic data. Our simulations show that the power of detecting TRs depends on the degree of their divergence, and repeat characteristics such as the length of the minimal repeat unit and their number in tandem. To reconcile the diverse predictions of current algorithms, we propose and evaluate several statistical criteria for measuring the quality of predicted repeat units. In particular, we propose a model-based phylogenetic classifier, entailing a maximum-likelihood estimation of the repeat divergence. Applied in conjunction with the state of the art detectors, our statistical classification scheme for inferred repeats allows to filter out false-positive predictions. Since different algorithms appear to specialize at predicting TRs with certain properties, we advise applying multiple detectors with subsequent filtering to obtain the most complete set of genuine repeats.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 92
    Publication Date: 2012-11-25
    Description: MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miR’s targets is a considerable bioinformatic challenge of great importance for inferring the miR’s function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methods—it identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs’ function in a specific context.
    Keywords: Computational Methods, Genomics
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    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 93
    Publication Date: 2013-02-20
    Description: High-throughput sequencing is increasingly being used in combination with bisulfite (BS) assays to study DNA methylation at nucleotide resolution. Although several programmes provide genome-wide alignment of BS-treated reads, the resulting information is not readily interpretable and often requires further bioinformatic steps for meaningful analysis. Current post-alignment BS-sequencing programmes are generally focused on the gene-specific level, a restrictive feature when analysis in the non-coding regions, such as enhancers and intergenic microRNAs, is required. Here, we present Genome Bisulfite Sequencing Analyser (GBSA— http://ctrad-csi.nus.edu.sg/gbsa ), a free open-source software capable of analysing whole-genome bisulfite sequencing data with either a gene-centric or gene-independent focus. Through analysis of the largest published data sets to date, we demonstrate GBSA’s features in providing sequencing quality assessment, methylation scoring, functional data management and visualization of genomic methylation at nucleotide resolution. Additionally, we show that GBSA’s output can be easily integrated with other high-throughput sequencing data, such as RNA-Seq or ChIP-seq, to elucidate the role of methylated intergenic regions in gene regulation. In essence, GBSA allows an investigator to explore not only known loci but also all the genomic regions, for which methylation studies could lead to the discovery of new regulatory mechanisms.
    Keywords: Computational Methods, Genomics
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  • 94
    Publication Date: 2013-02-20
    Description: Computationally identifying effective biomarkers for cancers from gene expression profiles is an important and challenging task. The challenge lies in the complicated pathogenesis of cancers that often involve the dysfunction of many genes and regulatory interactions. Thus, sophisticated classification model is in pressing need. In this study, we proposed an efficient approach, called ellipsoidFN (ellipsoid Feature Net), to model the disease complexity by ellipsoids and seek a set of heterogeneous biomarkers. Our approach achieves a non-linear classification scheme for the mixed samples by the ellipsoid concept, and at the same time uses a linear programming framework to efficiently select biomarkers from high-dimensional space. ellipsoidFN reduces the redundancy and improves the complementariness between the identified biomarkers, thus significantly enhancing the distinctiveness between cancers and normal samples, and even between cancer types. Numerical evaluation on real prostate cancer, breast cancer and leukemia gene expression datasets suggested that ellipsoidFN outperforms the state-of-the-art biomarker identification methods, and it can serve as a useful tool for cancer biomarker identification in the future. The Matlab code of ellipsoidFN is freely available from http://doc.aporc.org/wiki/EllipsoidFN .
    Keywords: Computational Methods, Genomics
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  • 95
    Publication Date: 2013-02-02
    Description: Designing effective antisense sequences is a formidable problem. A method for predicting efficacious antisense holds the potential to provide fundamental insight into this biophysical process. More practically, such an understanding increases the chance of successful antisense design as well as saving considerable time, money and labor. The secondary structure of an mRNA molecule is believed to be in a constant state of flux, sampling several different suboptimal states. We hypothesized that particularly volatile regions might provide better accessibility for antisense targeting. A computational framework, GenAVERT was developed to evaluate this hypothesis. GenAVERT used UNAFold and RNAforester to generate and compare the predicted suboptimal structures of mRNA sequences. Subsequent analysis revealed regions that were particularly volatile in terms of intramolecular hydrogen bonding, and thus potentially superior antisense targets due to their high accessibility. Several mRNA sequences with known natural antisense target sites as well as artificial antisense target sites were evaluated. Upon comparison, antisense sequences predicted based upon the volatility hypothesis closely matched those of the naturally occurring antisense, as well as those artificial target sites that provided efficient down-regulation. These results suggest that this strategy may provide a powerful new approach to antisense design.
    Keywords: Computational Methods, Genomics
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  • 96
    Publication Date: 2013-02-02
    Description: Existence of some extra-genetic (epigenetic) codes has been postulated since the discovery of the primary genetic code. Evident effects of histone post-translational modifications or DNA methylation over the efficiency and the regulation of DNA processes are supporting this postulation. EMdeCODE is an original algorithm that approximate the genomic distribution of given DNA features (e.g. promoter, enhancer, viral integration) by identifying relevant ChIPSeq profiles of post-translational histone marks or DNA binding proteins and combining them in a supermark. EMdeCODE kernel is essentially a two-step procedure: (i) an expectation-maximization process calculates the mixture of epigenetic factors that maximize the Sensitivity (recall) of the association with the feature under study; (ii) the approximated density is then recursively trimmed with respect to a control dataset to increase the precision by reducing the number of false positives. EMdeCODE densities improve significantly the prediction of enhancer loci and retroviral integration sites with respect to previous methods. Importantly, it can also be used to extract distinctive factors between two arbitrary conditions. Indeed EMdeCODE identifies unexpected epigenetic profiles specific for coding versus non-coding RNA, pointing towards a new role for H3R2me1 in coding regions.
    Keywords: Computational Methods, Genomics
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  • 97
    Publication Date: 2013-02-02
    Description: Insertion and deletion polymorphisms (indels) are an important source of genomic variation in plant and animal genomes, but accurate genotyping from low-coverage and exome next-generation sequence data remains challenging. We introduce an efficient population clustering algorithm for diploids and polyploids which was tested on a dataset of 2000 exomes. Compared with existing methods, we report a 4-fold reduction in overall indel genotype error rates with a 9-fold reduction in low coverage regions.
    Keywords: Computational Methods, Genomics
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  • 98
    Publication Date: 2013-02-02
    Description: Conventional approaches to predict transcriptional regulatory interactions usually rely on the definition of a shared motif sequence on the target genes of a transcription factor (TF). These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices, which may match large numbers of sites and produce an unreliable list of target genes. To improve the prediction of binding sites, we propose to additionally use the unrelated knowledge of the genome layout. Indeed, it has been shown that co-regulated genes tend to be either neighbors or periodically spaced along the whole chromosome. This study demonstrates that respective gene positioning carries significant information. This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon. To optimize this combination, PreCisIon builds a strong gene target classifier by adaptively combining weak classifiers based on either local binding sequence or global gene position. This strategy generically paves the way to the optimized incorporation of any future advances in gene target prediction based on local sequence, genome layout or on novel criteria. With the current state of the art, PreCisIon consistently improves methods based on sequence information only. This is shown by implementing a cross-validation analysis of the 20 major TFs from two phylogenetically remote model organisms. For Bacillus subtilis and Escherichia coli , respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity of 60 and 56%. The newly predicted gene targets are demonstrated to be functionally consistent with previously known targets, as assessed by analysis of Gene Ontology enrichment or of the relevant literature and databases.
    Keywords: Computational Methods, Genomics
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  • 99
    Publication Date: 2013-02-02
    Description: microRNAs (miRNAs) are short non-coding regulatory RNA molecules. The activity of a miRNA in a biological process can often be reflected in the expression program that characterizes the outcome of the activity. We introduce a computational approach that infers such activity from high-throughput data using a novel statistical methodology, called minimum-mHG (mmHG), that examines mutual enrichment in two ranked lists. Based on this methodology, we provide a user-friendly web application that supports the statistical assessment of miRNA target enrichment analysis (miTEA) in the top of a ranked list of genes or proteins. Using miTEA, we analyze several target prediction tools by examining performance on public miRNA constitutive expression data. We also apply miTEA to analyze several integrative biology data sets, including a novel matched miRNA/mRNA data set covering nine human tissue types. Our novel findings include proposed direct activity of miR-519 in placenta, a direct activity of the oncogenic miR-15 in different healthy tissue types and a direct activity of the poorly characterized miR-768 in both healthy tissue types and cancer cell lines. The miTEA web application is available at http://cbl-gorilla.cs.technion.ac.il/miTEA/ .
    Keywords: Computational Methods, Genomics
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  • 100
    Publication Date: 2013-02-02
    Description: Sequence alignment of proteins and nucleic acids is a routine task in bioinformatics. Although the comparison of complete peptides, genes or genomes can be undertaken with a great variety of tools, the alignment of short DNA sequences and motifs entails pitfalls that have not been fully addressed yet. Here we confront the structural superposition of transcription factors with the sequence alignment of their recognized cis elements. Our goals are (i) to test TFcompare ( http://floresta.eead.csic.es/tfcompare ), a structural alignment method for protein–DNA complexes; (ii) to benchmark the pairwise alignment of regulatory elements; (iii) to define the confidence limits and the twilight zone of such alignments and (iv) to evaluate the relevance of these thresholds with elements obtained experimentally. We find that the structure of cis elements and protein–DNA interfaces is significantly more conserved than their sequence and measures how this correlates with alignment errors when only sequence information is considered. Our results confirm that DNA motifs in the form of matrices produce better alignments than individual sequences. Finally, we report that empirical and theoretically derived twilight thresholds are useful for estimating the natural plasticity of regulatory sequences, and hence for filtering out unreliable alignments.
    Keywords: Computational Methods, Genomics
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