Literature DB >> 15130932

THEA: ontology-driven analysis of microarray data.

C Pasquier1, F Girardot, K Jevardat de Fombelle, R Christen.   

Abstract

MOTIVATION: Microarray technology makes it possible to measure thousands of variables and to compare their values under hundreds of conditions. Once microarray data are quantified, normalized and classified, the analysis phase is essentially a manual and subjective task based on visual inspection of classes in the light of the vast amount of information available. Currently, data interpretation clearly constitutes the bottleneck of such analyses and there is an obvious need for tools able to fill the gap between data processed with mathematical methods and existing biological knowledge.
RESULTS: THEA (Tools for High-throughput Experiments Analysis) is an integrated information processing system allowing convenient handling of data. It allows to automatically annotate data issued from classification systems with selected biological information coming from a knowledge base and to either manually search and browse through these annotations or automatically generate meaningful generalizations according to statistical criteria (data mining). AVAILABILITY: The software is available on the website http://thea.unice.fr/

Mesh:

Substances:

Year:  2004        PMID: 15130932     DOI: 10.1093/bioinformatics/bth295

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


  10 in total

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8.  Signalling crosstalk at the leading edge controls tissue closure dynamics in the Drosophila embryo.

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  10 in total

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