| dc.contributor.author | Goffard, Nicolas | |
| dc.contributor.author | Frickey, Tancred | |
| dc.contributor.author | Imin, Nijat | |
| dc.contributor.author | Weiller, Georg | |
| dc.contributor.editor | Beyer, Andreas | |
| dc.contributor.editor | Schroeder, Michael | |
| dc.date.accessioned | 2019-04-03T12:07:33Z | |
| dc.date.available | 2019-04-03T12:07:33Z | |
| dc.date.issued | 2008 | |
| dc.identifier.isbn | 978-3-88579-226-0 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/21218 | |
| dc.description.abstract | Post-genomic data analysis represents a new challenge to link and interpret the vast amount of raw data obtained with transcriptomic or proteomic techniques in the context of metabolic pathways. We propose a new strategy with the help of a metabolic network graph to extend PathExpress, a web-based tool to interpret gene expression data, without being restricted to predefined pathways. We defined the Enzyme Neighbourhood as groups of linked enzymes, corresponding to a sub-network, to explore the metabolic network in order to identify the most relevant sub-networks affected in gene expression experiments. | en |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e. V. | |
| dc.relation.ispartof | German Conference on Bioinformatics | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-136 | |
| dc.title | Exploring the Enzyme Neighbourhood to interpret gene expression data | en |
| dc.type | Text/Conference Paper | |
| dc.pubPlace | Bonn | |
| mci.reference.pages | 21-29 | |
| mci.conference.sessiontitle | Regular Research Papers | |
| mci.conference.location | Dresden | |
| mci.conference.date | 09.-12.09.2008 | |