Literature DB >> 12075016

Visualizing metabolic activity on a genome-wide scale.

A C M Luyf1, J de Gast, A H C van Kampen.   

Abstract

MOTIVATION: To enhance the exploration of gene expression data in a metabolic context, one requires an application that allows the integration of this data and which represents this data in a (genome-wide) metabolic map. The layout of this metabolic map must be highly flexible to enable discoveries of biological phenomena. Moreover, it must allow the simultaneous representation of additional information about genes and enzymes. Since the layout and properties of existing maps did not fulfill our requirements, we developed a new way of representing gene expression data in metabolic charts.
RESULTS: ViMAc generates user-specified (genome-wide) metabolic maps to explore gene expression data. To enhance the interpretation of these maps information such as sub-cellular localization is included. ViMAc can be used to analyse human or yeast expression data obtained with DNA microarrays or SAGE. We introduce our metabolic map method and demonstrate how it can be applied to explore DNA microarray data for yeast. AVAILABILITY: ViMAc is freely available for academic institutions on request from the authors.

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Year:  2002        PMID: 12075016     DOI: 10.1093/bioinformatics/18.6.813

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  4 in total

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4.  MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data.

Authors:  Scott W Doniger; Nathan Salomonis; Kam D Dahlquist; Karen Vranizan; Steven C Lawlor; Bruce R Conklin
Journal:  Genome Biol       Date:  2003-01-06       Impact factor: 13.583

  4 in total

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