Home

Welcome to my homepage. I graduated from Minzu University of China, in 2005. I received my Ph.D. from Nankai University, Tianjin in 2010. After graduation, I joined the School of Mathematical Sciences of Nankai University.

My main research interests includes (not limited):

  • Machine learning/ Deep learnings application in bioinformatics.
  • AI for biology data sciences.
  • Prediction of protein/RNA structures and functions
  • Immunoinformatics .

Please contact me via gao #@# nankai.edu.cn

Position: Master students: who are interested in Bioinformatics, AI for biolocial science. You should be good at one of following software: Python/R/C++/matlab/Perl/C etc.

Selected Papaers

(# co-author * corresponding author)

[1]    Chen Y# Lin S# Yang S# Qi M, Ren Y, Tian C, Wang S, Yang Y, Gao J*, Zhao H.*Genetic and phenotypic associations of frailty with cardiovascular indicators and behavioral characteristics. J Adv Res. 2024 Jun 9:S2090-1232(24)00249-2. doi: 10.1016/j.jare.2024.06.012 IF: 11.4 Q1 . 

[2]    Zeng, Y., Wei, Z., Yuan, Q., Chen, S., Yu, W., Lu, Y., Gao, J.*, & Yang, Y.* (2023). Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model. Bioinformatics, 39(4). https://doi.org/10.1093/bioinformatics/btad187 IF: 4.4 Q1

[3]    Gao, J*., Zheng, S., Yao, M., & Wu, P. (2021). Precise estimation of residue relative solvent accessible area from Cα atom distance matrix using a deep learning method. Bioinformatics, 38(1), 94-98. https://doi.org/10.1093/bioinformatics/btab616 IF: 6.931 Q1

[4] Wang, J., Chen, X., Hu, H., Yao, M., Song, Y., Yang, A., Xu, X., Zhang, N., Gao, J.*, & Liu, B.* (2021). PCAT-1 facilitates breast cancer progression via binding to RACK1 and enhancing oxygen-independent stability of HIF-1α. Mol Ther Nucleic Acids, 24, 310-324. https://doi.org/10.1016/j.omtn.2021.02.034 IF:10.183 Q2

[5] Gao, J., Yang, Y., & Zhou, Y. (2016). Predicting the errors of predicted local backbone angles and non-local solvent- accessibilities of proteins by deep neural networks. Bioinformatics, 32(24), 3768-3773. https://doi.org/10.1093/bioinformatics/btw549 IF:7.307 Q1