Analyzing causal relationships in proteomic profiles using CausalPath

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buir.contributor.authorDoğrusöz, Uğur
buir.contributor.orcidDoğrusöz, Uğur|0000-0002-7153-0784
dc.citation.epage12en_US
dc.citation.issueNumber4en_US
dc.citation.spage1en_US
dc.citation.volumeNumber2en_US
dc.contributor.authorLuna, A.
dc.contributor.authorSiper, M. C.
dc.contributor.authorKorkut, A.
dc.contributor.authorDurupinar, F.
dc.contributor.authorAslan, J. E.
dc.contributor.authorSander, C.
dc.contributor.authorDemir, E.
dc.contributor.authorBabur, O.
dc.contributor.authorDoğrusöz, Uğur
dc.date.accessioned2021-12-28T09:26:55Z
dc.date.available2021-12-28T09:26:55Z
dc.date.issued2021-12-17
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractCausalPath (causalpath.org) evaluates proteomic measurements against prior knowledge of biological pathways and infers causality between changes in measured features, such as global protein and phospho-protein levels. It uses pathway resources to determine potential causality between observable omic features, which are called prior relations. The subset of the prior relations that are supported by the proteomic profiles are reported and evaluated for statistical significance. The end result is a network model of signaling that explains the patterns observed in the experimental dataset.en_US
dc.description.provenanceSubmitted by Esma Babayiğit (esma.babayigit@bilkent.edu.tr) on 2021-12-28T09:26:55Z No. of bitstreams: 1 Analyzing_causal_relationships_in_proteomicprofiles_using_CausalPath.pdf: 2733838 bytes, checksum: 96d91acd4610c63a29412b8e912360ef (MD5)en
dc.description.provenanceMade available in DSpace on 2021-12-28T09:26:55Z (GMT). No. of bitstreams: 1 Analyzing_causal_relationships_in_proteomicprofiles_using_CausalPath.pdf: 2733838 bytes, checksum: 96d91acd4610c63a29412b8e912360ef (MD5) Previous issue date: 2021-12-17en
dc.identifier.doi10.1016/j.xpro.2021.100955en_US
dc.identifier.issn2666-1667
dc.identifier.urihttp://hdl.handle.net/11693/76731
dc.language.isoEnglishen_US
dc.publisherCell Pressen_US
dc.relation.isversionofhttps://dx.doi.org/10.1016/j.xpro.2021.100955en_US
dc.source.titleSTAR Protocolsen_US
dc.subjectBioinformaticsen_US
dc.subjectProteomicsen_US
dc.subjectSystems biologyen_US
dc.titleAnalyzing causal relationships in proteomic profiles using CausalPathen_US
dc.typeArticleen_US

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