Jun Zhu, PhD is a professor in Department of Genetics and Genomic Sciences. Dr. Zhu was trained in both computer science and biomedical science. His research focuses on methodologies for integrating diverse data (e.g. genetic, genomic, transcriptomic, proteomic data and etc.) into probabilistic graphic networks for elucidating complex human diseases, as well as method development for analyzing and comparing disease-related networks. Before joining Mount Sinai, he worked in both industry (Amgen, Inc, and Rosetta/Merck & CO, Inc) and academia (Sage Bionetworks, and Fred Hutchinson Cancer Research Center).
Genetics, Genomics, Mathematical Modeling of Biomedical Systems, Mathematical and Computational Biology
Multi-Disciplinary Training Areas
Genetics and Genomic Sciences [GGS], Pharmacology and Therapeutics Discovery [PTD]
BE, Tsinghua University
MS, State University of New York at Albany
Ph D, State University of New York at Albany
For more details about Dr. Zhu’s research, visit Dr. Zhu’s Integrative Network Biology group .
The explosion of large-scale, high-throughput technologies in the biological sciences demands a comprehensive view of biological systems. Dr. Zhu’s research focuses on analyzing large-scale high-throughput data:
1. Method development in integrating diverse high-throughput data into probabilistic causal network models.
2. Method development in comparing multiple networks.
3. Method development in analyzing biological networks.
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.
Below are financial relationships with industry reported by Dr. Zhu during 2020 and/or 2021. Please note that this information may differ from information posted on corporate sites due to timing or classification differences.
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