title: Metabolic module mining based on Independent Component Analysis in Arabidopsis thaliana.
abstract: Independent Component Analysis (ICA) has been introduced as one of the useful tools for gene-functional discovery in animals. However, this approach has been poorly utilized in the plant sciences. In the present study, we have exploited ICA combined with pathway enrichment analysis to address the statistical challenges associated with genome-wide analysis in plant system. To generate an Arabidopsis metabolic platform, we collected 4,373 Affy-metrix ATH1 microarray datasets. Out of the 3,232 metabolic genes and transcription factors, 99.47% of these genes were identified in at least one component, indicating the coverage of most of the metabolic pathways by the components. During the metabolic pathway enrichment analysis, we found components that indicate an independent regulation between the isoprenoid biosynthesis pathways. We also utilized this analysis tool to investigate some transcription factors involved in secondary cell wall biogenesis. This approach has identified remarkably more transcription factors compared to previously reported analysis tools. A website providing user-friendly searching and downloading of the entire dataset analyzed by ICA is available at                    http://kimjy.gnu.ac.kr/ICA.files/slide0002.htm                                    . ICA combined with pathway enrichment analysis might provide a powerful approach for the extraction of the components responsible for a biological process of interest in plant systems.
authors.affiliation: Division of Applied Life Science (Brain Korea 21-World Class University Program), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju, 660-701, Korea.
authors.forename: Xiao
authors.initials: X
authors.lastname: Han
authors.forename: Cong
authors.initials: C
authors.lastname: Chen
authors.forename: Tae Kyung
authors.initials: TK
authors.lastname: Hyun
authors.forename: Ritesh
authors.initials: R
authors.lastname: Kumar
authors.forename: Jae-Yean
authors.initials: JY
authors.lastname: Kim
mesh_terms: D017360:Arabidopsis / Q000235:genetics / Q000378:metabolism*; D029681:Arabidopsis Proteins / Q000235:genetics / Q000378:metabolism*; D002473:Cell Wall / Q000378:metabolism*; D057225:Data Mining / Q000379:methods*; D030541:Databases, Genetic; D018506:Gene Expression Regulation, Plant; D018745:Genome, Plant; D053858:Metabolic Networks and Pathways / Q000235:genetics; D008954:Models, Biological; D013729:Terpenes / Q000378:metabolism; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
chemical_list: D029681:Arabidopsis Proteins; D013729:Terpenes; D014157:Transcription Factors