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  • Computational Methods  (62)
  • Chromatin and Epigenetics  (39)
  • Oxford University Press  (101)
  • 1
    Publication Date: 2015-09-19
    Description: Sequence alignment is a long standing problem in bioinformatics. The Basic Local Alignment Search Tool (BLAST) is one of the most popular and fundamental alignment tools. The explosive growth of biological sequences calls for speedup of sequence alignment tools such as BLAST. To this end, we develop high speed BLASTN (HS-BLASTN), a parallel and fast nucleotide database search tool that accelerates MegaBLAST—the default module of NCBI-BLASTN. HS-BLASTN builds a new lookup table using the FMD-index of the database and employs an accurate and effective seeding method to find short stretches of identities (called seeds) between the query and the database. HS-BLASTN produces the same alignment results as MegaBLAST and its computational speed is much faster than MegaBLAST. Specifically, our experiments conducted on a 12-core server show that HS-BLASTN can be 22 times faster than MegaBLAST and exhibits better parallel performance than MegaBLAST. HS-BLASTN is written in C++ and the related source code is available at https://github.com/chenying2016/queries under the GPLv3 license.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 2
    Publication Date: 2015-05-29
    Description: Model evaluation is a necessary step for better prediction and design of 3D RNA structures. For proteins, this has been widely studied and the knowledge-based statistical potential has been proved to be one of effective ways to solve this problem. Currently, a few knowledge-based statistical potentials have also been proposed to evaluate predicted models of RNA tertiary structures. The benchmark tests showed that they can identify the native structures effectively but further improvements are needed to identify near-native structures and those with non-canonical base pairs. Here, we present a novel knowledge-based potential, 3dRNAscore, which combines distance-dependent and dihedral-dependent energies. The benchmarks on different testing datasets all show that 3dRNAscore are more efficient than existing evaluation methods in recognizing native state from a pool of near-native states of RNAs as well as in ranking near-native states of RNA models.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 3
    Publication Date: 2016-06-21
    Description: Defining chromatin interaction frequencies and topological domains is a great challenge for the annotations of genome structures. Although the chromosome conformation capture (3C) and its derivative methods have been developed for exploring the global interactome, they are limited by high experimental complexity and costs. Here we describe a novel computational method, called CITD, for de novo prediction of the chromatin interaction map by integrating histone modification data. We used the public epigenomic data from human fibroblast IMR90 cell and embryonic stem cell (H1) to develop and test CITD, which can not only successfully reconstruct the chromatin interaction frequencies discovered by the Hi-C technology, but also provide additional novel details of chromosomal organizations. We predicted the chromatin interaction frequencies, topological domains and their states (e.g. active or repressive) for 98 additional cell types from Roadmap Epigenomics and ENCODE projects. A total of 131 protein-coding genes located near 78 preserved boundaries among 100 cell types are found to be significantly enriched in functional categories of the nucleosome organization and chromatin assembly. CITD and its predicted results can be used for complementing the topological domains derived from limited Hi-C data and facilitating the understanding of spatial principles underlying the chromosomal organization.
    Keywords: Chromatin and Epigenetics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 4
    Publication Date: 2016-06-21
    Description: The goal of pathway analysis is to identify the pathways that are significantly impacted when a biological system is perturbed, e.g. by a disease or drug. Current methods treat pathways as independent entities. However, many signals are constantly sent from one pathway to another, essentially linking all pathways into a global, system-wide complex. In this work, we propose a set of three pathway analysis methods based on the impact analysis, that performs a system-level analysis by considering all signals between pathways, as well as their overlaps. Briefly, the global system is modeled in two ways: (i) considering the inter-pathway interaction exchange for each individual pathways, and (ii) combining all individual pathways to form a global, system-wide graph. The third analysis method is a hybrid of these two models. The new methods were compared with DAVID, GSEA, GSA, PathNet, Crosstalk and SPIA on 23 GEO data sets involving 19 tissues investigated in 12 conditions. The results show that both the ranking and the P -values of the target pathways are substantially improved when the analysis considers the system-wide dependencies and interactions between pathways.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 5
    Publication Date: 2016-07-09
    Description: Bioinformatic analysis often produces large sets of genomic ranges that can be difficult to interpret in the absence of genomic context. Goldmine annotates genomic ranges from any source with gene model and feature contexts to facilitate global descriptions and candidate loci discovery. We demonstrate the value of genomic context by using Goldmine to elucidate context dynamics in transcription factor binding and to reveal differentially methylated regions (DMRs) with context-specific functional correlations. The open source R package and documentation for Goldmine are available at http://jeffbhasin.github.io/goldmine .
    Keywords: Computational Methods
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    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 6
    Publication Date: 2016-07-09
    Description: Dam identification (DamID) is a powerful technique to generate genome-wide maps of chromatin protein binding. Due to its high sensitivity, it is particularly suited to study the genome interactions of chromatin proteins in small tissue samples in model organisms such as Drosophila . Here, we report an intein-based approach to tune the expression level of Dam and Dam-fusion proteins in Drosophila by addition of a ligand to fly food. This helps to suppress possible toxic effects of Dam. In addition, we describe a strategy for genetically controlled expression of Dam in a specific cell type in complex tissues. We demonstrate the utility of the latter by generating a glia-specific map of Polycomb in small samples of brain tissue. These new DamID tools will be valuable for the mapping of binding patterns of chromatin proteins in Drosophila tissues and especially in cell lineages.
    Keywords: Chromatin and Epigenetics
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    Topics: Biology
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  • 7
    Publication Date: 2016-07-28
    Description: CCCTC-binding factor (CTCF) is a multi-functional protein that is assigned various, even contradictory roles in the genome. High-throughput sequencing-based technologies such as ChIP-seq and Hi-C provided us the opportunity to assess the multivalent functions of CTCF in the human genome. The location of CTCF-binding sites with respect to genomic features provides insights into the possible roles of this protein. Here we present the first genome-wide survey and characterization of three important functions of CTCF: enhancer insulator, chromatin barrier and enhancer linker. We developed a novel computational framework to discover the multivalent functions of CTCF based on chromatin state and three-dimensional chromatin architecture. We applied our method to five human cell lines and identified ~46 000 non-redundant CTCF sites related to the three functions. Disparate effects of these functions on gene expression were found and distinct genomic features of these CTCF sites were characterized in GM12878 cells. Finally, we investigated the cell-type specificities of CTCF sites related to these functions across five cell types. Our study provides new insights into the multivalent functions of CTCF in the human genome.
    Keywords: Computational Methods
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  • 8
    Publication Date: 2013-09-26
    Description: Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide only an overview of the aggregate of numerous cells. Computational approaches to de-mix a collective signal composed of the aberrations of a mixed cell population of a tumor sample into its individual components are not available. We propose an evolutionary framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. We have developed an algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation data sets. We applied TrAp to Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of single cells of the same tumor. Finally, we deconvolve sequencing data from eight acute myeloid leukemia patients and three distinct metastases of one melanoma patient to exhibit the evolutionary relationships of their subpopulations.
    Keywords: Computational Methods
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    Topics: Biology
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  • 9
    Publication Date: 2013-04-02
    Description: MicroRNAs (miRNAs) constitute an important class of small regulatory RNAs that are derived from distinct hairpin precursors (pre-miRNAs). In contrast to mature miRNAs, which have been characterized in numerous genome-wide studies of different organisms, research on global profiling of pre-miRNAs is limited. Here, using massive parallel sequencing, we have performed global characterization of both mouse mature and precursor miRNAs. In total, 87 369 704 and 252 003 sequencing reads derived from 887 mature and 281 precursor miRNAs were obtained, respectively. Our analysis revealed new aspects of miRNA/pre-miRNA processing and modification, including eight Ago2-cleaved pre-miRNAs, eight new instances of miRNA editing and exclusively 5' tailed mirtrons. Furthermore, based on the sequences of both mature and precursor miRNAs, we developed a miRNA discovery pipeline, miRGrep, which does not rely on the availability of genome reference sequences. In addition to 239 known mouse pre-miRNAs, miRGrep predicted 41 novel ones with high confidence. Similar as known ones, the mature miRNAs derived from most of these novel loci showed both reduced abundance following Dicer knockdown and the binding with Argonaute2. Evaluation on data sets obtained from Caenorhabditis elegans and Caenorhabditis sp.11 demonstrated that miRGrep could be widely used for miRNA discovery in metazoans, especially in those without genome reference sequences.
    Keywords: Computational Methods
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  • 10
    Publication Date: 2013-04-02
    Description: DNA methylation is one of the most important epigenetic alterations involved in the control of gene expression. Bisulfite sequencing of genomic DNA is currently the only method to study DNA methylation patterns at single-nucleotide resolution. Hence, next-generation sequencing of bisulfite-converted DNA is the method of choice to investigate DNA methylation profiles at the genome-wide scale. Nevertheless, whole genome sequencing for analysis of human methylomes is expensive, and a method for targeted gene analysis would provide a good alternative in many cases where the primary interest is restricted to a set of genes. Here, we report the successful use of a custom Agilent SureSelect Target Enrichment system for the hybrid capture of bisulfite-converted DNA. We prepared bisulfite-converted next-generation sequencing libraries, which are enriched for the coding and regulatory regions of 174 ADME genes (i.e. genes involved in the metabolism and distribution of drugs). Sequencing of these libraries on Illumina’s HiSeq2000 revealed that the method allows a reliable quantification of methylation levels of CpG sites in the selected genes, and validation of the method using pyrosequencing and the Illumina 450K methylation BeadChips revealed good concordance.
    Keywords: Chromatin and Epigenetics
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    Electronic ISSN: 1362-4962
    Topics: Biology
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