Data- and knowledge-based modeling of gene regulatory networks: an update

dc.contributor.authorLinde, Jörg
dc.contributor.authorSchulze, Sylvie
dc.contributor.authorHenkel, Sebastian G.
dc.contributor.authorGuthke, Reinhard
dc.date.accessioned2015-04-22T12:44:58Z
dc.date.available2015-04-22T12:44:58Z
dc.date.issued2015-03-02
dc.description.abstractGene regulatory network inference is a systems biology approach which predicts interactions between genes with the help of high-throughput data. In this review, we present current and updated network inference methods focusing on novel techniques for data acquisition, network inference assessment, network inference for interacting species and the integration of prior knowledge. After the advance of Next-Generation-Sequencing of cDNAs derived from RNA samples (RNA-Seq) we discuss in detail its application to network inference. Furthermore, we present progress for large-scale or even full-genomic network inference as well as for small-scale condensed network inference and review advances in the evaluation of network inference methods by crowdsourcing. Finally, we reflect the current availability of data and prior knowledge sources and give an outlook for the inference of gene regulatory networks that reflect interacting species, in particular pathogen-host interactions.en
dc.identifier.issn1611-2156
dc.identifier.urihttp://hdl.handle.net/2003/34059
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-7921
dc.language.isoen
dc.relation.ispartofseriesEXCLI Journal ; Vol. 14, 2015en
dc.subjectgene regulatory networksen
dc.subjectRNA-Seqen
dc.subjectprior knowledgeen
dc.subjectnetwork inferenceen
dc.subjectreverse engineeringen
dc.subjectmodelingen
dc.subject.ddc610
dc.titleData- and knowledge-based modeling of gene regulatory networks: an updateen
dc.typeText
dc.type.publicationtypearticle
dcterms.accessRightsopen access
eldorado.dnb.zdberstkatid2132560-1

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