title: 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.
authors.affiliation: Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark; Department of Cancer and Inflammation Research, Institute of Molecular Medicine, University of Southern Denmark, 5000 Odense, Denmark.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Alcaraz
authors.affiliation: Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark; Department of Cancer and Inflammation Research, Institute of Molecular Medicine, University of Southern Denmark, 5000 Odense, Denmark; Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, University of Southern Denmark, 5000 Odense, Denmark; Institute of Clinical Research, University of Southern Denmark, 5000 Odense, Denmark; Max Planck Institute for Informatics, 66123 Saarbrucken, Germany.
authors.forename: Markus
authors.initials: M
authors.lastname: List
authors.affiliation: Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark.
authors.forename: Martin
authors.initials: M
authors.lastname: Dissing-Hansen
authors.affiliation: Integrated Research Institute (IRI) for the Life Sciences and Department of Biology, Humboldt-Universitat zu Berlin, 10099 Berlin, Germany.
authors.forename: Marc
authors.initials: M
authors.lastname: Rehmsmeier
authors.affiliation: Institute of Clinical Research, University of Southern Denmark, 5000 Odense, Denmark; Epidemiology, Biostatistics and Biodemography, Institute of Public Health, University of Southern Denmark, 5000 Odense, Denmark.
authors.forename: Qihua
authors.initials: Q
authors.lastname: Tan
authors.affiliation: Department of Cancer and Inflammation Research, Institute of Molecular Medicine, University of Southern Denmark, 5000 Odense, Denmark; Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, University of Southern Denmark, 5000 Odense, Denmark.
authors.forename: Jan
authors.initials: J
authors.lastname: Mollenhauer
authors.affiliation: Department of Cancer and Inflammation Research, Institute of Molecular Medicine, University of Southern Denmark, 5000 Odense, Denmark; Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, University of Southern Denmark, 5000 Odense, Denmark; Department of Oncology, Odense University Hospital, 5000 Odense, Denmark.
authors.forename: Henrik J
authors.initials: HJ
authors.lastname: Ditzel
authors.affiliation: Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark; Max Planck Institute for Informatics, 66123 Saarbrucken, Germany.
authors.forename: Jan
authors.initials: J
authors.lastname: Baumbach
keywords: Pathway enrichment; algorithms; data integration; network analysis; systems biology