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. Yansu Wang, Murong Zhou, Quan Zou, Lei Xu. Machine learning for phytopathology: from the molecular scale towards the network scale. Briefings in Bioinformatics. Accepted
  2. Zheng Chen, Zijie Shen, Da Zhao, Lei Xu, Lijun Zhang, Quan Zou. Genome-wide analysis of LysM-containing gene family in Wheat: evolution and duplications during development and denfences. Genes. 2020, 12(1):31
  3. Zhibin Lv, Hui Ding, Lei Wang, Quan Zou*. A Convolutional Neural Network Using Dinucleotide One-hot Encoder for identifying DNA N6-Methyladenine Sites in the Rice Genome. Neurocomputing. 2021,422:214-221 (web server)
  4. Zheng Chen, Zijie Shen, Lei Xu, Da Zhao, Quan Zou*. Regulator network analysis of rice and maize yield- related genes. Frontiers in Cell and Developmental Biology. 2020, 8: 621464
  5. Mengting Niu, Yuan Lin*, Quan Zou*. SgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks. Plant Molecular Biology. DOI: 10.1007/s11103-020-01102-y
  6. Zijie Shen, Yuan Lin*, Quan Zou*. Transcription factors-DNA interactions in rice: identification and verification. Briefings in Bioinformatics. 2020, 21(3): 946-956 (SCI, IF2018=9.101, PMID:31091308)
  7. Sanwen Sun, Chunyu Wang, Hui Ding, Quan Zou*. Machine learning and its applications in plant molecular studies. Briefings in Functional Genomics. 2020, 19(1): 40-48 (SCI, IF2018=3.133)
  8. Changli Feng, Quan Zou*, Donghua Wang*. Using a Low Correlation High Orthogonality Feature Set and Machine Learning Methods to Identify Plant Pentatricopeptide Repeat Coding Gene/Protein. Neurocomputing. Doi: 10.1016/j.neucom.2020.02.079 (SCI, IF2018=4.072)
  9. Qianfei Huang, Jun Zhang, Leyi Wei, Fei Guo*, Quan Zou*. 6mA-RicePred: A method for identifying DNA N6-methyladenine sites in the rice genome based on feature fusion. Frontiers in Plant Science. 2020, 11: 4 (data) (SCI, IF2018=4.106)
  10. Jiang, J., F. Xing, C. Wang, and X.Zeng*. "Identification and Analysis of Rice Yield-Related Candidate Genes by Walking on the Functional Network." Frontiers in Plant Science 2018, 9:1685. (SCI, IF2018=4.106, PMID: 30524460) [web server] (EndNote)
  11. Jiang, J., F. Xing, X. Zeng, and Q. Zou*. "RicyerDB: A Database for Collecting Rice Yield-Related Genes with Biological Analysis." International Journal of Biological Sciences 14, no. 8 (2018): 965-70. (SCI, IF2018= 4.067, PMID: 29989091) [web server] (EndNote)
  12. 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)
  13. 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)