Robust de novo pathway enrichment with KeyPathwayMiner 5: [version 1; peer review: 2 approved]

Nicolas Alcaraz, Markus List, Martin Dissing-Hansen, Marc Rehmsmeier, Qihua Tan, Jan Mollenhauer, Henrik Ditzel, Jan Baumbach

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Abstract

Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks that are enriched for differentially active entities from a series of molecular profiles encoded as binary indicator matrices. Since interaction networks constantly evolve, an important question is how robust the extracted results are when the network is modified. We enable users to study this effect through several network perturbation techniques and over a range of perturbation degrees. In addition, users may now provide a gold-standard set to determine how enriched extracted pathways are with relevant genes compared to randomized versions of the original network.
Original languageEnglish
Article number1531
JournalF1000Research
Volume5
Number of pages9
ISSN2046-1402
DOIs
Publication statusPublished - 2016

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