Hao Lin Hui Ding Research Scientist Students Visiting Scholars Alumni Position

Shi-Shi Yuan Ph.D. candidate

Shi-Shi Yuan is a Ph.D. candidate of Center for Informational Biology and the Key Laboratory for NeuroInformation of Ministry of Education in UESTC (Supervisor: Hao Lin). His research focus is: digital health and identifation of protein sequence function.

E-mail: yuanshishi000@gmail.com;626164476@qq.com


Education and Training

2022-Present      Ph.D. candidate in Biomedical Engineering (Direction: Bioinformatics)
University of Electronic Science and Technology, Sichuan, China

2020-2022           M.Sc. in Biology (Direction: Bioinformatics)
University of Electronic Science and Technology, Sichuan, China

2016-2020           B.Sc. in Biotechnology & B.Eng. in Computer Science and Technology
University of Electronic Science and Technology, Sichuan, China

 

Published Papers

10. Dong Gao, Liping Ren, Yu-Duo Hao, Nalini Schaduangrat, Xiao-Wei Liu, Shi-Shi Yuan, Yu-He Yang, Yan Wang*, Watshara Shoombuatong*, Hui Ding*. (2024) The role of ncRNA regulatory mechanisms in diseases—case on gestational diabetes. Briefings in Bioinformatics, 25(1): bbad489. (2023 IF: 9.5) [Full Text]

9. Hong-Qi Zhang, Shang-Hua Liu, Rui Li, Jun-Wen Yu, Dong-Xin Ye, Shi-Shi Yuan, Hao Lin*, Cheng-Bing Huang*, and Hua Tang*. (2024) MIBPred: Ensemble Learning-Based Metal Ion-Binding Protein Classifier. ACS Omega, 9(7): 8439-8447. (2023 IF: 4.1) [Full Text] [Github]

8. Wen Zhu, Shi-Shi Yuan, Jian Li, Cheng-Bing Huang, Hao Lin*, Bo Liao*. (2023) A First Computational Frame for Recognizing Heparin-Binding Protein. Diagnostics, 13(14): 2465. (2022 IF: 3.6) [Full Text]

7. Yu-He Yang, Cai-Yi Ma, Dong Gao, Xiao-Wei Liu, Shi-Shi Yuan, Hui Ding*. (2023) i2OM: Toward a better prediction of 2'-O-methylation in human RNA. International Journal of Biological Macromolecules, 239: 124247. (2022 IF: 8.2) [Full Text] [Websever]

6. Shi-Shi Yuan, Dong Gao, Xue-Qin Xie, Cai-Yi Ma, Wei Su, Zhao-Yue Zhang*, Yan Zheng*, Hui Ding*. (2022) IBPred: A sequence-based predictor for identifying ion binding protein in phage. Computational and Structural Biotechnology Journal, 20: 4942-4951. (2021 IF: 6.155) [Full Text] [Github]

5. Hao Lv, Yang Zhang, Jia-Shu Wang, Shi-Shi Yuan, Zi-Jie Sun, Fu-Ying Dao, Zheng-Xing Guan, Hao Lin*, Ke-Jun Deng*. (2022) iRice-MS: An integrated XGBoost model for detecting multitype post-translational modification sites in rice. Briefings in Bioinformatics, 23(1): bbab486. (2021 IF: 13.994) [Full Text] [Websever]

4. Yu-He Yang, Jia-Shu Wang, Shi-Shi Yuan, Meng-Lu Liu, Wei Su, Zhao-Yue Zhang*, Hao Lin*. (2022) A Survey for Predicting ATP Binding Residues of Proteins Using Machine Learning Methods. Current Medicinal Chemistry, 29(5): 789-806. (2021 IF: 4.740) [Full Text]

3. Hasan Zulfiqar, Zi-Jie Sun, Qing-Lai Huang, Shi-Shi Yuan, Hao Lv, Fu-Ying Dao, Hao Lin*, Yan-Wen Li*. (2022) Deep-4mCW2V: A sequence-based predictor to identify N4-methylcytosine sites in Escherichia coli. Methods, 203: 558-563. (2021 IF: 4.647) [Full Text]

2. Hasan Zulfiqar, Shi-Shi Yuan, Qing-Lai Huang, Zi-Jie Sun, Fu-Ying Dao, Xiao-Long Yu*, Hao Lin*. (2021) Identification of cyclin protein using gradient boost decision tree algorithm. Computational and Structural Biotechnology Journal, 19: 4123-4131. (2020 IF: 7.271) [Full Text]

1. Dan Zhang, Hua-Dong Chen, Hasan Zulfiqar, Shi-Shi Yuan, Zhao-Yue Zhang*, Ke-Jun Deng*. (2021) iBLP: An XGBoost-Based Predictor for Identifying Bioluminescent Proteins. Computational and Mathematical Methods in Medicine, 2021: 6664362. (2020 IF: 2.238) [Full Text]