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  • Artikel  (1.569)
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  • Oxford University Press  (1.569)
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  • 1
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    ll-ACHRB: a scalable algorithm for sampling the feasible solution space of metabolic networks (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: Motivation: Random sampling of the solution space has emerged as a popular tool to explore and infer properties of large metabolic networks. However, conventional sampling approaches commonly used do not eliminate thermodynamically unfeasible loops. Results: In order to overcome this limitation, we developed an efficient sampling algorithm called loopless Artificially Centered Hit-and-Run on a Box (ll-ACHRB). This algorithm is inspired by the Hit-and-Run on a Box algorithm for uniform sampling from general regions, but employs the directions of choice approach of Artificially Centered Hit-and-Run. A novel strategy for generating feasible warmup points improved both sampling efficiency and mixing. ll-ACHRB shows overall better performance than current strategies to generate feasible flux samples across several models. Furthermore, we demonstrate that a failure to eliminate unfeasible loops greatly affects sample statistics, in particular the correlation structure. Finally, we discuss recommendations for the interpretation of sampling results and possible algorithmic improvements. Availability and implementation: Source code for MATLAB and OCTAVE including examples are freely available for download at http://www.aibn.uq.edu.au/cssb-resources under Software. Optimization runs can use Gurobi Optimizer (by default if available) or GLPK (included with the algorithm). Contact: lars.nielsen@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 2
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    On genomic repeats and reproducibility (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: Results: Here, we present a comprehensive analysis on the reproducibility of computational characterization of genomic variants using high throughput sequencing data. We reanalyzed the same datasets twice, using the same tools with the same parameters, where we only altered the order of reads in the input (i.e. FASTQ file). Reshuffling caused the reads from repetitive regions being mapped to different locations in the second alignment, and we observed similar results when we only applied a scatter/gather approach for read mapping—without prior shuffling. Our results show that, some of the most common variation discovery algorithms do not handle the ambiguous read mappings accurately when random locations are selected. In addition, we also observed that even when the exact same alignment is used, the GATK HaplotypeCaller generates slightly different call sets, which we pinpoint to the variant filtration step. We conclude that, algorithms at each step of genomic variation discovery and characterization need to treat ambiguous mappings in a deterministic fashion to ensure full replication of results. Availability and Implementation: Code, scripts and the generated VCF files are available at DOI:10.5281/zenodo.32611. Contact: calkan@cs.bilkent.edu.tr Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 3
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    The spatiotemporal order of signaling events unveils the logic of development signaling (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: Motivation: Animals from worms and insects to birds and mammals show distinct body plans; however, the embryonic development of diverse body plans with tissues and organs within is controlled by a surprisingly few signaling pathways. It is well recognized that combinatorial use of and dynamic interactions among signaling pathways follow specific logic to control complex and accurate developmental signaling and patterning, but it remains elusive what such logic is, or even, what it looks like. Results: We have developed a computational model for Drosophila eye development with innovated methods to reveal how interactions among multiple pathways control the dynamically generated hexagonal array of R8 cells. We obtained two novel findings. First, the coupling between the long-range inductive signals produced by the proneural Hh signaling and the short-range restrictive signals produced by the antineural Notch and EGFR signaling is essential for generating accurately spaced R8s. Second, the spatiotemporal orders of key signaling events reveal a robust pattern of lateral inhibition conducted by Ato-coordinated Notch and EGFR signaling to collectively determine R8 patterning. This pattern, stipulating the orders of signaling and comparable to the protocols of communication, may help decipher the well-appreciated but poorly defined logic of developmental signaling. Availability and implementation: The model is available upon request. Contact: hao.zhu@ymail.com Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 4
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    GenomeRunner web server: regulatory similarity and differences define the functional impact of SNP sets (2016)
    Oxford University Press
    Details
    Publikationsdatum: 2016-07-30
    Beschreibung: Motivation: The growing amount of regulatory data from the ENCODE, Roadmap Epigenomics and other consortia provides a wealth of opportunities to investigate the functional impact of single nucleotide polymorphisms (SNPs). Yet, given the large number of regulatory datasets, researchers are posed with a challenge of how to efficiently utilize them to interpret the functional impact of SNP sets. Results: We developed the GenomeRunner web server to automate systematic statistical analysis of SNP sets within a regulatory context. Besides defining the functional impact of SNP sets, GenomeRunner implements novel regulatory similarity/differential analyses, and cell type-specific regulatory enrichment analysis. Validated against literature- and disease ontology-based approaches, analysis of 39 disease/trait-associated SNP sets demonstrated that the functional impact of SNP sets corresponds to known disease relationships. We identified a group of autoimmune diseases with SNPs distinctly enriched in the enhancers of T helper cell subpopulations, and demonstrated relevant cell type-specificity of the functional impact of other SNP sets. In summary, we show how systematic analysis of genomic data within a regulatory context can help interpreting the functional impact of SNP sets. Availability and Implementation: GenomeRunner web server is freely available at http://www.integrativegenomics.org/ . Contact: mikhail.dozmorov@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 5
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    Drug-induced adverse events prediction with the LINCS L1000 data (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: Motivation: Adverse drug reactions (ADRs) are a central consideration during drug development. Here we present a machine learning classifier to prioritize ADRs for approved drugs and pre-clinical small-molecule compounds by combining chemical structure (CS) and gene expression (GE) features. The GE data is from the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 dataset that measured changes in GE before and after treatment of human cells with over 20 000 small-molecule compounds including most of the FDA-approved drugs. Using various benchmarking methods, we show that the integration of GE data with the CS of the drugs can significantly improve the predictability of ADRs. Moreover, transforming GE features to enrichment vectors of biological terms further improves the predictive capability of the classifiers. The most predictive biological-term features can assist in understanding the drug mechanisms of action. Finally, we applied the classifier to all 〉20 000 small-molecules profiled, and developed a web portal for browsing and searching predictive small-molecule/ADR connections. Availability and Implementation: The interface for the adverse event predictions for the 〉20 000 LINCS compounds is available at http://maayanlab.net/SEP-L1000/ . Contact: avi.maayan@mssm.edu Supplementary information : Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 6
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    ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: Motivation: Environmental dissemination of antibiotic resistance genes (ARGs) has become an increasing concern for public health. Metagenomics approaches can effectively detect broad profiles of ARGs in environmental samples; however, the detection and subsequent classification of ARG-like sequences are time consuming and have been severe obstacles in employing metagenomic methods. We sought to accelerate quantification of ARGs in metagenomic data from environmental samples. Results: A Structured ARG reference database (SARG) was constructed by integrating ARDB and CARD, the two most commonly used databases. SARG was curated to remove redundant sequences and optimized to facilitate query sequence identification by similarity. A database with a hierarchical structure (type-subtype-reference sequence) was then constructed to facilitate classification (assigning ARG-like sequence to type, subtype and reference sequence) of sequences identified through similarity search. Utilizing SARG and a previously proposed hybrid functional gene annotation pipeline, we developed an online pipeline called ARGs-OAP for fast annotation and classification of ARG-like sequences from metagenomic data. We also evaluated and proposed a set of criteria important for efficiently conducting metagenomic analysis of ARGs using ARGs-OAP. Availability and Implementation: Perl script for ARGs-OAP can be downloaded from https://github.com/biofuture/Ublastx_stageone . ARGs-OAP can be accessed through http://smile.hku.hk/SARGs . Contact: zhangt@hku.hk or tiedjej@msu.edu Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 7
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    chromPlot: visualization of genomic data in chromosomal context (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: : Visualizing genomic data in chromosomal context can help detecting errors in data processing and may suggest new hypotheses to be tested. Here, we report a new tool for displaying large and diverse genomic data along chromosomes. The software is implemented in R so that visualization can be easily integrated with its numerous packages for processing genomic data. It supports simultaneous visualization of multiple tracks of data. Large genomic regions such as QTLs or synteny tracts may be shown along histograms of number of genes, genetic variants, or any other type of genomic element. Tracks can also contain values for continuous or categorical variables and the user can choose among points, connected lines, colored segments, or histograms for representing data. chromPlot takes data from tables in data.frame in GRanges formats. The information necessary to draw chromosomes for mouse and human is included with the package. For other organisms, chromPlot can read Gap and cytoBandIdeo tables from the UCSC Genome Browser. We present common use cases here, and a full tutorial is included as the package’s vignette. Availability and Implementation: chromPlot is distributed under a GLP2 licence at http://www.bioconductor.org . Contact: raverdugo@u.uchile.cl Supplementary information: Supplementary data are available at Bioinformatics online.
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    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 8
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    BLESS 2: accurate, memory-efficient and fast error correction method (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: : The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow to handle reads from large genomes. We have developed a new version of BLESS to improve runtime and accuracy while maintaining a small memory usage. The new version, called BLESS 2, has an error correction algorithm that is more accurate than BLESS, and the algorithm has been parallelized using hybrid MPI and OpenMP programming. BLESS 2 was compared with five top-performing tools, and it was found to be the fastest when it was executed on two computing nodes using MPI, with each node containing twelve cores. Also, BLESS 2 showed at least 11% higher gain while retaining the memory efficiency of the previous version for large genomes. Availability and implementation: Freely available at https://sourceforge.net/projects/bless-ec Contact: dchen@illinois.edu Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 9
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    Deep models for brain EM image segmentation: novel insights and improved performance (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: Motivation: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation. Results: In this work, we proposed a novel design of DNNs for this task. We trained a pixel classifier that operates on raw pixel intensities with no preprocessing to generate probability values for each pixel being a membrane or not. Although the use of neural networks in image segmentation is not completely new, we developed novel insights and model architectures that allow us to achieve superior performance on EM image segmentation tasks. Our submission based on these insights to the 2D EM Image Segmentation Challenge achieved the best performance consistently across all the three evaluation metrics. This challenge is still ongoing and the results in this paper are as of June 5, 2015. Availability and Implementation : https://github.com/ahmed-fakhry/dive Contact : sji@eecs.wsu.edu
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    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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  • 10
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    HilbertCurve: an R/Bioconductor package for high-resolution visualization of genomic data (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: : Hilbert curves enable high-resolution visualization of genomic data on a chromosome- or genome-wide scale. Here we present the HilbertCurve package that provides an easy-to-use interface for mapping genomic data to Hilbert curves. The package transforms the curve as a virtual axis, thereby hiding the details of the curve construction from the user. HilbertCurve supports multiple-layer overlay that makes it a powerful tool to correlate the spatial distribution of multiple feature types. Availability and implementation: The HilbertCurve package and documentation are freely available from the Bioconductor project: http://www.bioconductor.org/packages/devel/bioc/html/HilbertCurve.html Contact: m.schlesner@dkfz.de Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
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    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
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