
Li Shen, PhD
- ASSOCIATE PROFESSOR | Neuroscience
Research Topics:
Bioinformatics, Biomedical Informatics, Computational Biology, Epigenomics, Image Analysis, Mathematical Modeling of Biomedical Systems, Mathematical and Computational BiologyDr. Shen joined the Department of Neuroscience at the Icahn School of Medicine at Mount Sinai in 2009 with a Ph.D. in computer science. He is currently associate professor of bioinformatics. He has made contributions to epigenomics in brain diseases and bioinformatic tools development. His current research interests include the applications of machine learning in healthcare and genomics. He has more than 100 publications with >7,700 total citations. See his Google scholar page for a full list of his publications. Visit Li Shen's Laboratory of Bioinformatics for more information on his research activities.
Multi-Disciplinary Training Area
Genetics and Data Science [GDS]Education
BS, Fudan University
PhD, Nanyang Technological University
Postdoc, University of California San Diego
-
2006
Burroughs Wellcome Funds for Interfaces in Science -
2000
IBM ViaVoice National Campus Application Contest Excellence Prize
Large-scale next-generation sequencing data analysis
Our research scope includes but is not limited to: ChIP-seq, RNA-seq, small RNA-seq and DNA methyl-seq. From 2009-2016, my group analyzed more than 6,000 NGS samples with a total storage of more than 50TB. The results have generated numerous publications in top-tier journals, such as Nature, Neuron, Nature Neuroscience, Genome Biology and PNAS.
Software for next-generation sequencing analysis
We have developed two popular programs: diffReps (https://github.com/shenlab-sinai/diffreps) for ChIP-seq differential analysis and ngs.plot (https://github.com/shenlab-sinai/ngsplot) for data mining and visualization of NGS data. Please visit our group Github page at: https://github.com/shenlab-sinai.
Machine learning
Dr. Shen has made several contributions to the open-source machine learning community: https://github.com/lishen/my-contributions-to-open-ml. He has also done some research in using machine learning for automated genome segmentation: http://dx.doi.org/10.1101/034579. Machine learning has and will always be an important tool for his research and a focus of research on its own.
Physicians and scientists on the faculty of the Icahn School of Medicine at Mount Sinai often interact with pharmaceutical, device and biotechnology companies to improve patient care, develop new therapies and achieve scientific breakthroughs. In order to promote an ethical and transparent environment for conducting research, providing clinical care and teaching, Mount Sinai requires that salaried faculty inform the School of their relationships with such companies.
Dr. Shen did not report having any of the following types of financial relationships with industry during 2020 and/or 2021: consulting, scientific advisory board, industry-sponsored lectures, service on Board of Directors, participation on industry-sponsored committees, equity ownership valued at greater than 5% of a publicly traded company or any value in a privately held company. Please note that this information may differ from information posted on corporate sites due to timing or classification differences.
Mount Sinai's faculty policies relating to faculty collaboration with industry are posted on our website. Patients may wish to ask their physician about the activities they perform for companies.