Research

李克峰 Li Kefeng

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 Biography

Dr. Li is currently an associate professor at Faculty of Applied Sciences, Macao Polytechnic University. His research fields mainly include multi-omics data integration and its application in understanding the pathogenesis of chronic diseases, discovering novel drug targets, and evaluating drug toxicity. He is also interested in deep learning-based medical data analysis and developing novel multi-biomarker models for complex disorders. Dr. Li has developed one of the first next-generation broad-spectrum, single-injection metabolomics and exposomics methods. Until now, he has published over 100 papers in related fields, including World Psychiatry (5-year IF: 66.7, same below), PNAS (IF:13.45), Advanced Science (IF:18.94), BMC Medicine (IF:11.13), JACC Cardiovasc Interv. (IF:10.55), Environ Int. (IF:13.24), Environ Sci Technol. (IF:12.15), and Crit Rev Food Sci Nutr. (IF:11.21). He has received grants from NSFC and other sources and serves as a grant reviewer for the U.S. EPA and the Israeli Ministry of Agriculture & Rural Development. He is also on the editorial board of Current Pharmaceutical Design and a peer reviewer for over a dozen decent journals (IF > 10), such as Nature Communications and Annals of Internal Medicine.

 Education and Experiences

Education:
2007 - 2012   Ph.D., Michigan Technological University, USA
2004 - 2007   M.Sc., Tianjin University, Major in Pharmacognosy
2000 - 2004   B.Sc., Tianjin University of Traditional Chinese Medicine, Major in TCM

Professional experiences:
2023-now   Associate Professor, Faculty of Applied Sciences, Macao Polytechnic University
2012-2022  Postdoctoral Fellow, Project Scientist, University of California, San Diego, USA

 Research Interests

• Development of new metabolomics methods and data analysis based on deep-learning and causal inference approaches
• Discovery of shared mechanisms and novel drug targets across various complex diseases using multi-omics integration
• AI-based medical and healthcare data analysis
• Treatment of complex psychiatric disorders such as autism and depression using TCM, and natural products

 Selected Recent Publications (First or corresponding author)

1. Li K#, Henry HY Tong#, Chen Y#, Sun Y, Wang J. The emerging roles of next-generation metabolomics in critical care nutrition. Crit Rev Food Sci Nutr. 2022. doi: 10.1080/10408398.2022.2113761. (5-year IF:11.21, #co-first, same below).
2. J Zheng, K Wang, Y Wang*, Li K*. Precautions for study design and data interpretation of clinical metabolomics. Proc Natl Acad Sci USA, 2022, 119(5): e2118654119. (IF: 13.45,*corresponding author).
3. Wang QS, Yan K, Li KD, Gao LN, Wang X, Liu H, Zhang Z, Li K*, Cui YL*. Targeting hippocampal phospholipid and tryptophan metabolism for antidepressant-like effects of albiflorin. Phytomedicine, 2021, 92:15735. (IF: 6.14).
4. Cui S, Li L, Zhang Y, Lu J, Wang X, Song X, Liu J* and Li K*. Machine learning identifies metabolic signatures that predict the risk of recurrent angina in remitted patients after percutaneous coronary intervention: A multicenter prospective cohort study. Adv Sci. 2021; 8:2003893. (IF: 18.94).
5. Li J, Yang Z, Qiu H, Wang Y, Jian L, Ji J and Li K*. Anxiety and depression among general population in China at the peak of the COVID-19 epidemic. World Psychiatry. 2020;19:249-250. (IF: 66.75).
6. Ji J, Song L, Wang J, Yang Z, Yan H, Li T, Yu L, Jian L, Jiang F, Li J*, Zheng J* and Li K*. Association between urinary per- and poly-fluoroalkyl substances and COVID-19 susceptibility. Environ Int. 2021; 153:106524. (IF: 13.24).
7. Li K*, JC Naviaux, SS Lingampelly, Wang L, JM Monk, CM Taylor, C Ostle, S Batten, RK Naviaux*. Historical biomonitoring of pollution trends in the North Pacific using archived samples from the continuous plankton recorder survey. Sci Total Environ. 2022, 161222. doi: 10.1016/j.scitotenv.2022.161222. (IF: 10.75).
8. Li K, Schon M, Naviaux JC, Monk JM, Alchus-Laiferova N, Wang L, Straka I, Matejicka P, Valkovic P, Ukropec J, et al. Cerebrospinal fluid and plasma metabolomics of acute endurance exercise. FASEB J. 2022; 36:e22408. (IF: 6.10).
9. Li K, Bertrand K, Naviaux JC, Monk JM, Wells A, Wang L, Lingampelly SS, Naviaux RK, Chambers C. Metabolomic and exposomic biosignatures in human milk that predict risk of future neurodevelopmental delay. Pediatr. Res. 2022, doi: 10.1038/s41390-022-02283-6. (IF: 3.95).
10. Wang J, Sun Y, Teng S and Li K*. Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation. BMC Med. 2020; 18:83. (IF: 11.13).
11. Yang Z, Jian L, Qiu H, Zhang C, Cheng S, Ji J, Wang Y, Li J*, and Li K*. Understanding complex functional wiring patterns in major depressive disorder through brain functional connectome. Transl Psychiatry 2021; 11(1): 526. (IF: 7.97).
12. Cui S#, Li K#*, Ang L, Liu J, Cui L, Song X, Lv S and Mahmud E*. Plasma phospholipids and sphingolipids identify stent restenosis after percutaneous coronary intervention. JACC Cardiovasc Interv. 2017; 10:1307-1316. (IF: 10.55).