Title
EXPath: a database of comparative expression analysis inferring metabolic pathways for plants.
Abstract
In general, the expression of gene alters conditionally to catalyze a specific metabolic pathway. Microarray-based datasets have been massively produced to monitor gene expression levels in parallel with numerous experimental treatments. Although several studies facilitated the linkage of gene expression data and metabolic pathways, none of them are amassed for plants. Moreover, advanced analysis such as pathways enrichment or how genes express under different conditions is not rendered.Therefore, EXPath was developed to not only comprehensively congregate the public microarray expression data from over 1000 samples in biotic stress, abiotic stress, and hormone secretion but also allow the usage of this abundant resource for coexpression analysis and differentially expression genes (DEGs) identification, finally inferring the enriched KEGG pathways and gene ontology (GO) terms of three model plants: Arabidopsis thaliana, Oryza sativa, and Zea mays. Users can access the gene expression patterns of interest under various conditions via five main functions (Gene Search, Pathway Search, DEGs Search, Pathways/GO Enrichment, and Coexpression analysis) in EXPath, which are presented by a user-friendly interface and valuable for further research.In conclusion, EXPath, freely available at http://expath.itps.ncku.edu.tw, is a database resource that collects and utilizes gene expression profiles derived from microarray platforms under various conditions to infer metabolic pathways for plants.
Year
DOI
Venue
2015
10.1186/1471-2164-16-S2-S6
BMC Genomics
Keywords
Field
DocType
Gene Ontology, KEGG Pathway, Methyl Jasmonate, Microarray Gene Expression Data, Coexpression Analysis
Arabidopsis,Microarray,Gene,Biology,Proteomics,Metabolic pathway,Transcriptome,Gene expression,Bioinformatics,Genetics,DNA microarray
Journal
Volume
Issue
ISSN
16 Suppl 2
S-2
1471-2164
Citations 
PageRank 
References 
2
0.37
13
Authors
6
Name
Order
Citations
PageRank
Chia-Hung Chien120.37
Chi-Nga Chow292.28
Nai-Yun Wu360.83
Yi-Fan Chiang-Hsieh481.91
Ping-Fu Hou560.83
Wen-Chi Chang61488.92