EXPath 2.0: An Updated Database for Integrating High-Throughput Gene Expression Data with Biological Pathways

Kuan Chieh Tseng, Guan Zhen Li, Yu Cheng Hung, Chi Nga Chow, Nai Yun Wu, Yi Ying Chie, Han Qin Zheng, Tzong Yi Lee, Po Li Kuo, Song Bin Chang, Wen Chi Chang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Co-expressed genes tend to have regulatory relationships and participate in similar biological processes. Construction of gene correlation networks from microarray or RNA-seq expression data has been widely applied to study transcriptional regulatory mechanisms and metabolic pathways under specific conditions. Furthermore, since transcription factors (TFs) are critical regulators of gene expression, it is worth investigating TFs on the promoters of co-expressed genes. Although coexpressed genes and their related metabolic pathways can be easily identified from previous resources, such as EXPath and EXPath Tool, this information is not simultaneously available to identify their regulatory TFs. EXPath 2.0 is an updated database for the investigation of regulatory mechanisms in various plant metabolic pathways with 1,881 microarray and 978 RNA-seq samples. There are six significant improvements in EXPath 2.0: (i) the number of species has been extended from three to six to include Arabidopsis, rice, maize, Medicago, soybean and tomato; (ii) gene expression at various developmental stages have been added; (iii) construction of correlation networks according to a group of genes is available; (iv) hierarchical figures of the enriched Gene Ontology (GO) terms are accessible; (v) promoter analysis of genes in a metabolic pathway or correlation network is provided; and (vi) user's gene expression data can be uploaded and analyzed. Thus, EXPath 2.0 is an updated platform for investigating gene expression profiles and metabolic pathways under specific conditions. It facilitates users to access the regulatory mechanisms of plant biological processes. The new version is available at http://EXPath.itps.ncku.edu.tw.

Original languageEnglish
Pages (from-to)1818-1827
Number of pages10
JournalPlant and Cell Physiology
Issue number10
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • Physiology
  • Plant Science
  • Cell Biology


Dive into the research topics of 'EXPath 2.0: An Updated Database for Integrating High-Throughput Gene Expression Data with Biological Pathways'. Together they form a unique fingerprint.

Cite this