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

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 o...

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Veröffentlicht in:Bioinformatics Jg. 29; H. 4; S. 520 - 522
Hauptverfasser: Kramer, Frank, Bayerlová, Michaela, Klemm, Florian, Bleckmann, Annalen, Beißbarth, Tim
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England 15.02.2013
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ISSN:1367-4803, 1367-4811, 1367-4811, 1460-2059
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Zusammenfassung: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. Contact:  frank.kramer@med.uni-goettingen.de Supplementary information:  Supplementary data are available at Bioinformatics online.
Bibliographie:ObjectType-Article-1
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content type line 23
ISSN:1367-4803
1367-4811
1367-4811
1460-2059
DOI:10.1093/bioinformatics/bts710