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PMID: 18160330 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Review

Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

Trends in plant science ·Vol. 13 ·No. 1 ·2008-01-00 ·Pages 36-43

Saito K, Hirai MY, Yonekura-Sakakibara K

Abstract

Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

MeSH Terms
Computational Biology Databases, Genetic Gene Expression Profiling/methods Genomics/methods Plants/genetics,metabolism Systems Biology
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Saito Kazuki
RIKEN Plant Science Center, Tsurumi-ku, Yokohama 230-0045, Japan. [email protected]
Hirai Masami Y
Yonekura-Sakakibara Keiko
Article Info
Journal
Trends in plant science
Abbr.
Trends Plant Sci
ISSN
1360-1385
Published
2008-01-00
Epub
2007-00-21
Pages
36-43
Language
English
Region
England
NLM ID
9890299
Subset
IM
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