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Expression profiles of metabolic models to predict compartmentation of enzymes in multi-compartmental systems

dc.contributor.authorChokkathukalam, Achuthanunni
dc.contributor.authorPoolman, Marc
dc.contributor.authorFerrazzi, Chiara
dc.contributor.authorFell, David
dc.contributor.editorGrosse, Ivo
dc.contributor.editorNeumann, Steffen
dc.contributor.editorPosch, Stefan
dc.contributor.editorSchreiber, Falk
dc.contributor.editorStadler, Peter
dc.date.accessioned2019-02-20T09:48:28Z
dc.date.available2019-02-20T09:48:28Z
dc.date.issued2009
dc.description.abstractEnzymes and other proteins coded by nuclear genes are targeted towards various compartments in the plant cell. Here, we describe a method by which localisation of enzymes in a plant cell may be predicted based on their transcription profile in conjunction with analysis of the structure of the metabolic network. This method uses reaction correlation coefficients to identify reactions in a metabolic model that carry similar flux. First a correlation matrix for the expression of genes of interest is calculated and the columns clustered hierarchically using the correlation coefficient. The rows clustered using reaction correlation coefficients. In the resulting matrix, we show that the genes in a particular compartment are clustered together and compartmental predictions, with respect to a reference gene can be readily made.en
dc.identifier.isbn978-3-88579-251-2
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/20299
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofGerman conference on bioinformatics 2009
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-157
dc.titleExpression profiles of metabolic models to predict compartmentation of enzymes in multi-compartmental systemsen
dc.typeText/Conference Paper
gi.citation.endPage162
gi.citation.publisherPlaceBonn
gi.citation.startPage153
gi.conference.date28th to 30th September 2009
gi.conference.locationHalle-Wittenberg
gi.conference.sessiontitleRegular Research Papers

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