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dc.contributor.authorBurger, Bramen_US
dc.contributor.authorHernández Sánchez, Luis Franciscoen_US
dc.contributor.authorLereim, Ragnhild Reehorsten_US
dc.contributor.authorBarsnes, Haralden_US
dc.contributor.authorVaudel, Marcen_US
dc.date.accessioned2020-06-11T11:36:53Z
dc.date.available2020-06-11T11:36:53Z
dc.date.issued2018
dc.PublishedBurger B, Hernández Sánchez LF, Lereim RR, Barsnes H, Vaudel M. Analyzing the Structure of Pathways and Its Influence on the Interpretation of Biomedical Proteomics Data Sets. Journal of Proteome Research. 2018;17(11):3801-3809eng
dc.identifier.issn1535-3907
dc.identifier.issn1535-3893
dc.identifier.urihttps://hdl.handle.net/1956/22539
dc.description.abstractBiochemical pathways are commonly used as a reference to conduct functional analysis on biomedical omics data sets, where experimental results are mapped to knowledgebases comprising known molecular interactions collected from the literature. Due to their central role, the content of the functional knowledgebases directly influences the outcome of pathway analyses. In this study, we investigate the structure of the current pathway knowledge, as exemplified by Reactome, discuss the consequences for biological interpretation, and outline possible improvements in the use of pathway knowledgebases. By providing a view of the underlying protein interaction network, we aim to help pathway analysis users manage their expectations and better identify possible artifacts in the results.en_US
dc.language.isoengeng
dc.publisherAmerican Chemical Societyeng
dc.titleAnalyzing the Structure of Pathways and Its Influence on the Interpretation of Biomedical Proteomics Data Setsen_US
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2019-11-11T14:40:46Z
dc.description.versionacceptedVersionen_US
dc.rights.holderCopyright 2018 American Chemical Society
dc.identifier.doihttps://doi.org/10.1021/acs.jproteome.8b00464
dc.identifier.cristin1630489
dc.source.journalJournal of Proteome Research
dc.relation.projectBergens forskningsstiftelse: BFS2016REK02
dc.relation.projectNorges forskningsråd: 251235
dc.identifier.citationJournal of Proteome Research. 2018, 17 (11), 3801-3809.


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