Li Tingting

Basic Information
Li Tingting. She is an associate professor of Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center. Our lab focuses on phase separation and transition within biological context. We developed a series of databases and prediction tools & methods fusing multiple bioinformation and explores potential drug target from phase separation perspective.
Doctor Li was the sub-project leader of the National Key Research and Development Program of China, leading 4 projects funded by the National Natural Science Foundation and participating 3 projects of National Key Research & Development Program as backbone investigator. She also serves as a member of Bioinformatics and Artificial Life Committee of Chinese Association of Artificial Intelligence, member of Computational Biology and Bioinformatics Committee of Chinese Society of Biotechnology, member of Bioinformatics Committee of China Computer Federation and council member of the 1st Biomolecular Phase Separation & Transition Committee of Biophysical Society of China.
Education Experience
1999/09 – 2003/07, Bachelor of Engineering, Department of Automation, Xi’An JiaoTong University.
2003/09 – 2009/01, Ph.D. of Bioinformatics, Department of Automation, Tsinghua University.
Work Experience
2009/08 - 2012/07, Assistant Professor, Department of Biomedical Informatics, Peking University Health Science Center.
2012/08 - 2022/07, Associate Professor, Department of Biomedical Informatics, Peking University Health Science Center.
2022/08 - 2024/01, Research fellow, Associate Professor (tenure), Department of Biomedical Informatics, Peking University Health Science Center.
2024/02 - Now, Boya Distinguished Professor, Full Professor (tenure), Department of Biomedical Informatics, Peking University Health Science Center.
Research Interest
1. Composition and dynamic regulation of bimolecular condensates
2. Computational analysis on phase separation and phase transition
3. Abnormal phase separation and diseases
4. Regulatory networks of protein post-translational modification
5. Integrative mining of mass spectrum data, next-generation sequencing data and other omics data