Jun Zhu, PhD is a professor in Department of Genetics and Genomic Sciences and a member of Institute of Genomics and Multiscale Biology. 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 Data Science [GDS], 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.
Yoo S, Huang T, Campbell JD, Lee E, Tu Z, Geraci MW, Powell CA, Schadt EE, Spira A, Zhu J. MODMatcher: multi-omics data matcher for integrative genomic analysis. PLoS computational biology 2014 Aug; 10(8).
Narayanan M, Huynh JL, Wang K, Yang X, Yoo S, McElwee J, Zhang B, Zhang C, Lamb JR, Xie T, Suver C, Molony C, Melquist S, Johnson AD, Fan G, Stone DJ, Schadt EE, Casaccia P, Emilsson V, Zhu J. Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases. Molecular systems biology 2014; 10(7).
Zhu J, Chen Y, Leonardson AS, Wang K, Lamb JR, Emilsson V, Schadt EE. Characterizing dynamic changes in the human blood transcriptional network. PLoS computational biology 2010 Feb; 6(2).
Leonardson AS, Zhu J, Chen Y, Wang K, Lamb JR, Reitman M, Emilsson V, Schadt EE. The effect of food intake on gene expression in human peripheral blood. Human molecular genetics 2010 Jan; 19(1).
Zhang W, Zhu J, Schadt EE, Liu JS. A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules. PLoS computational biology 2010 Jan; 6(1).
Wang K, Narayanan M, Zhong H, Tompa M, Schadt EE, Zhu J. Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases. PLoS computational biology 2009 Dec; 5(12).
Narayanan M, Vetta A, Schadt EE, Zhu J. Simultaneous clustering of multiple gene expression and physical interaction datasets. PLoS computational biology 2010 Apr; 6(4).
Tu Z, Argmann C, Wong KK, Mitnaul LJ, Edwards S, Sach IC, Zhu J, Schadt EE. Integrating siRNA and protein-protein interaction data to identify an expanded insulin signaling network. Genome research 2009 Jun; 19(6).
Zhu J, Zhang B, Smith EN, Drees B, Brem RB, Kruglyak L, Bumgarner RE, Schadt EE. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nature genetics 2008 Jul; 40(7).
Chen Y, Zhu J, Lum PY, Yang X, Pinto S, MacNeil DJ, Zhang C, Lamb J, Edwards S, Sieberts SK, Leonardson A, Castellini LW, Wang S, Champy MF, Zhang B, Emilsson V, Doss S, Ghazalpour A, Horvath S, Drake TA, Lusis AJ, Schadt EE. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar; 452(7186).
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Dr.Zhu did not report having any of the following types of financial relationships with industry during 2017 and/or 2018: 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.
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