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BiopLib and BiopTools--a C programming library and toolset for manipulating protein structure (2015)

Porter, C. T., Martin, A. C. R.

Oxford University Press

In: Bioinformatics

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Publikationsdatum: 2015-12-10

Beschreibung: : We describe BiopLib, a mature C programming library for manipulating protein structure, and BiopTools, a set of command-line tools which exploit BiopLib. The library also provides a small number of functions for handling protein sequence and general purpose programming and mathematics. BiopLib transparently handles PDBML (XML) format and standard PDB files. BiopTools provides facilities ranging from renumbering atoms and residues to calculation of solvent accessibility. Availability and implementation: BiopLib and BiopTools are implemented in standard ANSI C. The core of the BiopLib library is a reliable PDB parser that handles alternate occupancies and deals with compressed PDB files and PDBML files automatically. The library is designed to be as flexible as possible, allowing users to handle PDB data as a simple list of atoms, or in a structured form using chains, residues and atoms. Many of the BiopTools command-line tools act as filters, taking a PDB (or PDBML) file as input and producing a PDB (or PDBML) file as output. All code is open source and documented using Doxygen. It is provided under the GNU Public Licence and is available from the authors’ web site or from GitHub. Contact: andrew@bioinf.org.uk

Print ISSN: 1367-4803

Digitale ISSN: 1460-2059

Thema: Biologie , Informatik , Medizin

Publiziert von Oxford University Press

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Automated structural classification of lipids by machine learning (2015)

Taylor, R., Miller, R. H., Miller, R. D., Porter, M., Dalgleish, J., Prince, J. T.

Oxford University Press

In: Bioinformatics

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Publikationsdatum: 2015-02-27

Beschreibung: Motivation: Modern lipidomics is largely dependent upon structural ontologies because of the great diversity exhibited in the lipidome, but no automated lipid classification exists to facilitate this partitioning. The size of the putative lipidome far exceeds the number currently classified, despite a decade of work. Automated classification would benefit ongoing classification efforts by decreasing the time needed and increasing the accuracy of classification while providing classifications for mass spectral identification algorithms. Results: We introduce a tool that automates classification into the LIPID MAPS ontology of known lipids with 〉95% accuracy and novel lipids with 63% accuracy. The classification is based upon simple chemical characteristics and modern machine learning algorithms. The decision trees produced are intelligible and can be used to clarify implicit assumptions about the current LIPID MAPS classification scheme. These characteristics and decision trees are made available to facilitate alternative implementations. We also discovered many hundreds of lipids that are currently misclassified in the LIPID MAPS database, strongly underscoring the need for automated classification. Availability and implementation: Source code and chemical characteristic lists as SMARTS search strings are available under an open-source license at https://www.github.com/princelab/lipid_classifier . Contact: ryanmt@byu.net Supplementary information: Supplementary data are available at Bioinformatics online.

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Digitale ISSN: 1460-2059

Thema: Biologie , Informatik , Medizin

Publiziert von Oxford University Press

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ClusPro PeptiDock: efficient global docking of peptide recognition motifs using FFT (2017)

Porter, Kathryn A ; Xia, Bing ; Beglov, Dmitri ; [weitere]

Oxford University Press

In: Bioinformatics. 2017; 33(20): 3299-3301. Published 2017 Apr 18. doi: 10.1093/bioinformatics/btx216.

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Publikationsdatum: 2017-04-18

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Thema: Biologie , Informatik , Medizin

Publiziert von Oxford University Press

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BiopLib and BiopTools—a C programming library and toolset for manipulating protein structure (2015)

Porter, Craig T. ; Martin, Andrew C.R.

Oxford University Press

In: Bioinformatics. 2015; btv482. Published 2015 Aug 30. doi: 10.1093/bioinformatics/btv482. [early online release]

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Publikationsdatum: 2015-08-30

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Thema: Biologie , Informatik , Medizin

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ORE identifies extreme expression effects enriched for rare variants (2019)

Richter, F ; Hoffman, G E ; Manheimer, K B ; [weitere]

Oxford University Press

In: Bioinformatics. 2019; 35(20): 3906-3912. Published 2019 Mar 23. doi: 10.1093/bioinformatics/btz202.

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Publikationsdatum: 2019-03-23

Beschreibung: Motivation Non-coding rare variants (RVs) may contribute to Mendelian disorders but have been challenging to study due to small sample sizes, genetic heterogeneity and uncertainty about relevant non-coding features. Previous studies identified RVs associated with expression outliers, but varying outlier definitions were employed and no comprehensive open-source software was developed. Results We developed Outlier-RV Enrichment (ORE) to identify biologically-meaningful non-coding RVs. We implemented ORE combining whole-genome sequencing and cardiac RNAseq from congenital heart defect patients from the Pediatric Cardiac Genomics Consortium and deceased adults from Genotype-Tissue Expression. Use of rank-based outliers maximized sensitivity while a most extreme outlier approach maximized specificity. Rarer variants had stronger associations, suggesting they are under negative selective pressure and providing a basis for investigating their contribution to Mendelian disorders. Availability and implementation ORE, source code, and documentation are available at https://pypi.python.org/pypi/ore under the MIT license. Supplementary information Supplementary data are available at Bioinformatics online.

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Thema: Biologie , Informatik , Medizin

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Predicting the effects of SNPs on transcription factor binding affinity (2019)

Nishizaki, Sierra S ; Ng, Natalie ; Dong, Shengcheng ; [weitere]

Oxford University Press

In: Bioinformatics. 2019; Published 2019 Aug 02. doi: 10.1093/bioinformatics/btz612. [early online release]

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Publikationsdatum: 2019-08-02

Beschreibung: Motivation Genome-wide association studies have revealed that 88% of disease-associated single-nucleotide polymorphisms (SNPs) reside in noncoding regions. However, noncoding SNPs remain understudied, partly because they are challenging to prioritize for experimental validation. To address this deficiency, we developed the SNP effect matrix pipeline (SEMpl). Results SEMpl estimates transcription factor-binding affinity by observing differences in chromatin immunoprecipitation followed by deep sequencing signal intensity for SNPs within functional transcription factor-binding sites (TFBSs) genome-wide. By cataloging the effects of every possible mutation within the TFBS motif, SEMpl can predict the consequences of SNPs to transcription factor binding. This knowledge can be used to identify potential disease-causing regulatory loci. Availability and implementation SEMpl is available from https://github.com/Boyle-Lab/SEM_CPP. Supplementary information Supplementary data are available at Bioinformatics online.

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Thema: Biologie , Informatik , Medizin

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DeuteRater: a Tool for Quantifying Peptide Isotope Precision and Kinetic Proteomics (2017)

Naylor, Bradley C. ; Porter, Michael T. ; Wilson, Elise ; [weitere]

Oxford University Press

In: Bioinformatics. 2017; btx009. Published 2017 Jan 16. doi: 10.1093/bioinformatics/btx009. [early online release]

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Publikationsdatum: 2017-01-16

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Thema: Biologie , Informatik , Medizin

Publiziert von Oxford University Press

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Differential network enrichment analysis reveals novel lipid pathways in chronic kidney disease (2019)

Ma, Jing ; Karnovsky, Alla ; Afshinnia, Farsad ; [weitere]

Oxford University Press

In: Bioinformatics. 2019; 35(18): 3441-3452. Published 2019 Feb 14. doi: 10.1093/bioinformatics/btz114.

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Publikationsdatum: 2019-02-14

Beschreibung: Motivation Functional enrichment testing methods can reduce data comprising hundreds of altered biomolecules to smaller sets of altered biological ‘concepts’ that help generate testable hypotheses. This study leveraged differential network enrichment analysis methodology to identify and validate lipid subnetworks that potentially differentiate chronic kidney disease (CKD) by severity or progression. Results We built a partial correlation interaction network, identified highly connected network components, applied network-based gene-set analysis to identify differentially enriched subnetworks, and compared the subnetworks in patients with early-stage versus late-stage CKD. We identified two subnetworks ‘triacylglycerols’ and ‘cardiolipins-phosphatidylethanolamines (CL-PE)’ characterized by lower connectivity, and a higher abundance of longer polyunsaturated triacylglycerols in patients with severe CKD (stage ≥4) from the Clinical Phenotyping Resource and Biobank Core. These finding were replicated in an independent cohort, the Chronic Renal Insufficiency Cohort. Using an innovative method for elucidating biological alterations in lipid networks, we demonstrated alterations in triacylglycerols and cardiolipins-phosphatidylethanolamines that precede the clinical outcome of end-stage kidney disease by several years. Availability and implementation A complete list of NetGSA results in HTML format can be found at http://metscape.ncibi.org/netgsa/12345-022118/cric_cprobe/022118/results_cric_cprobe/main.html. The DNEA is freely available at https://github.com/wiggie/DNEA. Java wrapper leveraging the cytoscape.js framework is available at http://js.cytoscape.org. 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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