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Robust de novo pathway enrichment with KeyPathwayMiner 5.

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.

SUBMITTER: Alcaraz N

PROVIDER: S-EPMC4965696 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Robust de novo pathway enrichment with KeyPathwayMiner 5.

Alcaraz Nicolas N List Markus M Dissing-Hansen Martin M Rehmsmeier Marc M Tan Qihua Q Mollenhauer Jan J Ditzel Henrik J HJ Baumbach Jan J

F1000Research 20160628

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 robu ...[more]

PMID: 27540470

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