The identification and analysis the genes of crop yield traits are an essential but challenging task in bioinformatics research. We have developed a database of rice yield and identified candidates based on the database.

Friendly web servers were developed and maintained.
We manually searched the related databases and literature.
We proposed a computational systems biology approach for the identification of candidate genes via a random walk model on a PPI network with functional similarities.


Publications and Web Servers

  1. Zijie Shen, Yuan Lin*, Quan Zou*. Transcription factors-DNA interactions in rice: identification and verification. Briefings in Bioinformatics. doi: 10.1093/bib/bbz045(SCI, IF2017=6.302, PMID:31091308)
  2. Jiang, J., F. Xing, C. Wang, and X. Zeng*. "Identification and Analysis of Rice Yield-Related Candidate Genes by Walking on the Functional Network." Front Plant Sci 9 (2018): 1685. (SCI, IF= 3.677, PMID: 30524460) [web server] (EndNote)
  3. Jiang, J., F. Xing, X. Zeng, and Q. Zou*. "RicyerDB: A Database for Collecting Rice Yield-Related Genes with Biological Analysis." Int J Biol Sci 14, no. 8 (2018): 965-70. (SCI, IF= 4.057, PMID: 29989091) [web server] (EndNote)
  4. Jiang, J., F. Xing, X. Zeng, and Q. Zou*. "Investigating maize yield-related genes in multiple omics interaction network data." IEEE Trans Nanobioscience. (2019). (SCI, IF= 1.927, PMID: 31170079) (EndNote)
  5. Jiang, J., F. Xing, C. Wang, X. Zeng, and Q. Zou*. "Investigation and development of maize fused network analysis with multi-omics." Plant Physiol Biochem. (2019): 380-387. (SCI, IF= 3.404, PMID: 31220804) [web server] (EndNote)