Literature DB >> 23274212

rBiopaxParser--an R package to parse, modify and visualize BioPAX data.

Frank Kramer1, Michaela Bayerlová, Florian Klemm, Annalen Bleckmann, Tim Beissbarth.   

Abstract

MOTIVATION: Biological pathway data, stored in structured databases, is a useful source of knowledge for a wide range of bioinformatics algorithms and tools. The Biological Pathway Exchange (BioPAX) language has been established as a standard to store and annotate pathway information. However, use of these data within statistical analyses can be tedious. On the other hand, the statistical computing environment R has become the standard for bioinformatics analysis of large-scale genomics data. With this package, we hope to enable R users to work with BioPAX data and make use of the always increasing amount of biological pathway knowledge within data analysis methods.
RESULTS: rBiopaxParser is a software package that provides a comprehensive set of functions for parsing, viewing and modifying BioPAX pathway data within R. These functions enable the user to access and modify specific parts of the BioPAX model. Furthermore, it allows to generate and layout regulatory graphs of controlling interactions and to visualize BioPAX pathways. AVAILABILITY: rBiopaxParser is an open-source R package and has been submitted to Bioconductor.

Mesh:

Year:  2012        PMID: 23274212     DOI: 10.1093/bioinformatics/bts710

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  18 in total

1.  NetPathMiner: R/Bioconductor package for network path mining through gene expression.

Authors:  Ahmed Mohamed; Timothy Hancock; Canh Hao Nguyen; Hiroshi Mamitsuka
Journal:  Bioinformatics       Date:  2014-07-28       Impact factor: 6.937

2.  ndexr-an R package to interface with the network data exchange.

Authors:  Florian Auer; Zaynab Hammoud; Alexandr Ishkin; Dexter Pratt; Trey Ideker; Frank Kramer
Journal:  Bioinformatics       Date:  2018-02-15       Impact factor: 6.937

3.  A network-based kernel machine test for the identification of risk pathways in genome-wide association studies.

Authors:  Saskia Freytag; Juliane Manitz; Martin Schlather; Thomas Kneib; Christopher I Amos; Angela Risch; Jenny Chang-Claude; Joachim Heinrich; Heike Bickeböller
Journal:  Hum Hered       Date:  2014-01-14       Impact factor: 0.444

4.  Newly Constructed Network Models of Different WNT Signaling Cascades Applied to Breast Cancer Expression Data.

Authors:  Michaela Bayerlová; Florian Klemm; Frank Kramer; Tobias Pukrop; Tim Beißbarth; Annalen Bleckmann
Journal:  PLoS One       Date:  2015-12-03       Impact factor: 3.240

5.  Comparative study on gene set and pathway topology-based enrichment methods.

Authors:  Michaela Bayerlová; Klaus Jung; Frank Kramer; Florian Klemm; Annalen Bleckmann; Tim Beißbarth
Journal:  BMC Bioinformatics       Date:  2015-10-22       Impact factor: 3.169

6.  Visualisation of BioPAX Networks using BioLayout Express (3D).

Authors:  Derek W Wright; Tim Angus; Anton J Enright; Tom C Freeman
Journal:  F1000Res       Date:  2014-10-20

Review 7.  Tools for visualization and analysis of molecular networks, pathways, and -omics data.

Authors:  Jose M Villaveces; Prasanna Koti; Bianca H Habermann
Journal:  Adv Appl Bioinform Chem       Date:  2015-06-04

8.  A global microRNA screen identifies regulators of the ErbB receptor signaling network.

Authors:  Annabell Bischoff; Michaela Bayerlová; Michaela Strotbek; Simone Schmid; Tim Beissbarth; Monilola A Olayioye
Journal:  Cell Commun Signal       Date:  2015-01-29       Impact factor: 5.712

9.  PaxtoolsR: pathway analysis in R using Pathway Commons.

Authors:  Augustin Luna; Özgün Babur; Bülent Arman Aksoy; Emek Demir; Chris Sander
Journal:  Bioinformatics       Date:  2015-12-18       Impact factor: 6.937

10.  R-based software for the integration of pathway data into bioinformatic algorithms.

Authors:  Frank Kramer; Michaela Bayerlová; Tim Beißbarth
Journal:  Biology (Basel)       Date:  2014-02-07
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