Vis enkel innførsel

dc.contributor.authorHamzeiy, Hamid
dc.contributor.authorFerretti, Daniela
dc.contributor.authorRobles, Maria S.
dc.contributor.authorCox, Juergen
dc.date.accessioned2023-04-14T11:56:39Z
dc.date.available2023-04-14T11:56:39Z
dc.date.created2022-10-11T08:46:47Z
dc.date.issued2022
dc.identifier.issn2667-2375
dc.identifier.urihttps://hdl.handle.net/11250/3063116
dc.description.abstractWe introduce Metis, a new plugin for the Perseus software aimed at analyzing quantitative multi-omics data based on metabolic pathways. Data from different omics types are connected through reactions of a genome-scale metabolic-pathway reconstruction. Metabolite concentrations connect through the reactants, while transcript, protein, and protein post-translational modification (PTM) data are associated through the enzymes catalyzing the reactions. Supported experimental designs include static comparative studies and time-series data. As an example for the latter, we combine circadian mouse liver multi-omics data and study the contribution of cycles of phosphoproteome and metabolome to enzyme activity regulation. Our analysis resulted in 52 pairs of cycling phosphosites and metabolites connected through a reaction. The time lags between phosphorylation and metabolite peak show non-uniform behavior, indicating a major contribution of phosphorylation in the modulation of enzymatic activity.en_US
dc.language.isoengen_US
dc.publisherCell Pressen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titlePerseus plugin “Metis” for metabolic-pathway-centered quantitative multi-omics data analysis for static and time-series experimental designsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.source.articlenumber100198en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.1016/j.crmeth.2022.100198
dc.identifier.cristin2060301
dc.source.journalCell Reports Methodsen_US
dc.identifier.citationCell Reports Methods. 2022, 2 (4), 100198.en_US
dc.source.volume2en_US
dc.source.issue4en_US


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal