Literature DB >> 17251202

Approaches for extracting practical information from gene co-expression networks in plant biology.

Koh Aoki1, Yoshiyuki Ogata, Daisuke Shibata.   

Abstract

Gene co-expression, in many cases, implies the presence of a functional linkage between genes. Co-expression analysis has uncovered gene regulatory mechanisms in model organisms such as Escherichia coli and yeast. Recently, accumulation of Arabidopsis microarray data has facilitated a genome-wide inspection of gene co-expression profiles in this model plant. An approach using network analysis has provided an intuitive way to represent complex co-expression patterns between many genes. Co-expression network analysis has enabled us to extract modules, or groups of tightly co-expressed genes, associated with biological processes. Furthermore, integrated analysis of gene expression and metabolite accumulation has allowed us to hypothesize the functions of genes associated with specific metabolic processes. Co-expression network analysis is a powerful approach for data-driven hypothesis construction and gene prioritization, and provides novel insights into the system-level understanding of plant cellular processes.

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Year:  2007        PMID: 17251202     DOI: 10.1093/pcp/pcm013

Source DB:  PubMed          Journal:  Plant Cell Physiol        ISSN: 0032-0781            Impact factor:   4.927


  165 in total

1.  COXPRESdb in 2015: coexpression database for animal species by DNA-microarray and RNAseq-based expression data with multiple quality assessment systems.

Authors:  Yasunobu Okamura; Yuichi Aoki; Takeshi Obayashi; Shu Tadaka; Satoshi Ito; Takafumi Narise; Kengo Kinoshita
Journal:  Nucleic Acids Res       Date:  2014-11-11       Impact factor: 16.971

Review 2.  Coexpression landscape in ATTED-II: usage of gene list and gene network for various types of pathways.

Authors:  Takeshi Obayashi; Kengo Kinoshita
Journal:  J Plant Res       Date:  2010-04-10       Impact factor: 2.629

3.  Combining genetic diversity, informatics and metabolomics to facilitate annotation of plant gene function.

Authors:  Takayuki Tohge; Alisdair R Fernie
Journal:  Nat Protoc       Date:  2010-06-10       Impact factor: 13.491

4.  Exploring tomato gene functions based on coexpression modules using graph clustering and differential coexpression approaches.

Authors:  Atsushi Fukushima; Tomoko Nishizawa; Mariko Hayakumo; Shoko Hikosaka; Kazuki Saito; Eiji Goto; Miyako Kusano
Journal:  Plant Physiol       Date:  2012-02-03       Impact factor: 8.340

Review 5.  Bioinformatic landscapes for plant transcription factor system research.

Authors:  Yijun Wang; Wenjie Lu; Dexiang Deng
Journal:  Planta       Date:  2015-12-30       Impact factor: 4.116

6.  Comparative co-expression network analysis extracts the SlHSP70 gene affecting to shoot elongation of tomato.

Authors:  Nam Tuan Vu; Ken Kamiya; Atsushi Fukushima; Shuhei Hao; Wang Ning; Tohru Ariizumi; Hiroshi Ezura; Miyako Kusano
Journal:  Plant Biotechnol (Tokyo)       Date:  2019-09-25       Impact factor: 1.133

7.  A regulon conserved in monocot and dicot plants defines a functional module in antifungal plant immunity.

Authors:  Matt Humphry; Pawel Bednarek; Birgit Kemmerling; Serry Koh; Mónica Stein; Ulrike Göbel; Kurt Stüber; Mariola Pislewska-Bednarek; Ann Loraine; Paul Schulze-Lefert; Shauna Somerville; Ralph Panstruga
Journal:  Proc Natl Acad Sci U S A       Date:  2010-11-22       Impact factor: 11.205

Review 8.  Web-queryable large-scale data sets for hypothesis generation in plant biology.

Authors:  Siobhan M Brady; Nicholas J Provart
Journal:  Plant Cell       Date:  2009-04-28       Impact factor: 11.277

9.  Gene and metabolite regulatory network analysis of early developing fruit tissues highlights new candidate genes for the control of tomato fruit composition and development.

Authors:  Fabien Mounet; Annick Moing; Virginie Garcia; Johann Petit; Michael Maucourt; Catherine Deborde; Stéphane Bernillon; Gwénaëlle Le Gall; Ian Colquhoun; Marianne Defernez; Jean-Luc Giraudel; Dominique Rolin; Christophe Rothan; Martine Lemaire-Chamley
Journal:  Plant Physiol       Date:  2009-01-14       Impact factor: 8.340

10.  The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.

Authors:  Sofie Van Landeghem; Stefanie De Bodt; Zuzanna J Drebert; Dirk Inzé; Yves Van de Peer
Journal:  Plant Cell       Date:  2013-03-26       Impact factor: 11.277

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