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Inferring regulatory systems with noisy pathway information

dc.contributor.authorSpieth, Christian
dc.contributor.authorStreichert, Felix
dc.contributor.authorSpeern, Nora
dc.contributor.authorZell, Andreas
dc.contributor.editorTorda, Andrew
dc.contributor.editorKurtz, Stefan
dc.contributor.editorRarey, Matthias
dc.date.accessioned2019-08-27T08:22:37Z
dc.date.available2019-08-27T08:22:37Z
dc.date.issued2005
dc.description.abstractWith increasing number of pathways available in public databases, the process of inferring gene regulatory networks becomes more and more feasible. The major problem of most of these pathways is that they are very often faulty or describe only parts of a regulatory system due to limitations of the experimental techniques or due to a focus specifically only on a subnetwork of a larger process. To address this issue, we propose a new multi-objective evolutionary algorithm in this paper, which infers gene regulatory systems from experimental microarray data by incorporating known pathways from publicly available databases. These pathways are used as an initial template for creating suitable models of the regulatory network and are then refined by the algorithm. With this approach, we were able to infer regulatory systems with incorporation of pathway information that is incomplete or even faulty.en
dc.identifier.isbn3-88579-400-4
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/24934
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofGerman Conference on Bioinformatics 2005 (GCB 2005)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-71
dc.titleInferring regulatory systems with noisy pathway informationen
dc.typeText/Conference Paper
gi.citation.endPage202
gi.citation.publisherPlaceBonn
gi.citation.startPage193
gi.conference.date5.-7. Oktober 2005
gi.conference.locationHamburg
gi.conference.sessiontitleRegular Research Papers

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