Dr. Zhang is currently an associate professor of the Department of Genetics and Genomic Sciences and a member of Institute of Genomics and Multiscale Biology. Dr. Zhang’s extensive experience in electrical engineering, computer science and computational biology empowers him to build up highly predictive models for very complex data from handwritten document images to large-scale cancer genomic data. Over the past decade, Dr. Zhang has developed and significantly contributed a series of influential gene network inference algorithms which have been extensively used for identification of novel pathways and gene targets, as well as development of drugs for a variety of human diseases such as cancer, atherosclerosis, Alzheimer's, obesity and diabetes. His latest research that uncovered dramatic changes in gene-gene interaction patterns in Alzheimer’s disease and pinpointed an immune/microglia gene network as the top pathway causally linked to the disease was just published in Cell. His recent research that sheds a new light on targeted therapies against breast cancer was featured by the Second AACR International Conference on Frontiers in Basic Cancer Research (San Francisco, September 14-18, 2011). His work on predicting genetic interactions was identified by Nature Biotechnology as one of the breakthroughs in the field of computational biology in 2010. The discovery of a gene cluster that is causally linked to obesity and diabetes was highlighted in Nature in 2008. His early research on image pattern recognition significantly contributed to several large-scale pattern recognition systems including U.S. Handwritten Address Identification System which has been adopted by US Postal Office. Dr. Zhang was a recipient of the Best Paper Award of ICDAR 2003 ─ the Seventh International Conference on Document Analysis and Recognition.
As a prolific researcher, Dr. Zhang has published a number of high profile papers in Nature, Science, Cell, Nature Genetics, and PNAS. As of April 2015, his publications have been cited 7131 times. Furthermore, he has been a leader of more than a dozen projects to identify novel drug targets for several pharmaceutical companies.For more information about Dr. Zhang's research, please visit http://research.mssm.edu/multiscalenetwork .
Adipose, Aging, Allergy, Alzheimer's Disease, Anti-Tumor Therapy, Apoptosis/Cell Death, Autism, Autophagy, Axonal Growth and Degeneration, Bioinformatics, Bone Biology, Bone Metabolism, Brain, Cancer, Cancer Genetics, Cell Cycle, Cerebral Cortex, Cognitive Neuroscience, Computational Neuroscience, Diabetes, Epigenetics, Gene Discovery, Gene Expressions, Gene Regulation, Gene Therapy, Genetics, Genetics of Movement disorders, Genomics, Glutamate (NMDA & AMPA) Receptors, Glutathione, Hippocampus, Human Genetics and Genetic Disorders, Image Analysis, Immunology, Infectious Disease, Inflammation, Liver, Lung, Mathematical Modeling of Biomedical Systems, Mathematical and Computational Biology, Memory, Metastasis, Microarray, Microglia, Mitosis, Molecular Biology, Motor Control, Obesity, Oncogenes, Prefrontal Cortex, Protein Complexes, Protein Folding, RNA Splicing & Processing, Tumor Suppressor Genes, Tumorigenesis
Multi-Disciplinary Training Areas
Genetics and Genomic Sciences [GGS], Neuroscience [NEU]
BE, Tongji University
MS, State University of New York at Buffalo
MS, Tsinghua University
PhD, State University of New York at Buffalo
Autonomous and Real-time Classification/Prediction Systems for Diagnosis and Treatments (ARCPS)
Enormous data from each single patient is being generated but it remains challenging how to make best use of the information for personalized medicine. ARCPS will take as inputs all pathological, clinical, genetic, genomic, proteomic, and metabolic information to classify patients, predict disease progression, determine drug response, and decide optimal treatments. Given the multi-modal nature of the input data, those complex high-dimension data types such as image, DNA, mRNA, protein and sequencing need go through different feature extractors to yield meaningful features for training and classification/prediction.
Reconstruction and Analysis of Multiscale Biological Networks
Advanced algorithms for reconstructing and analyzing multiscale biological networks are being developed to effectively and efficiently uncover novel targets, pathways and mechanisms driving complex human diseases including cancer, obesity, diabetes, cardiovascular and neurodegenerative disease. These data-driven drivers and pathways can be used to establish global driver-disease and pathway-disease connectivity maps that will be further utilized to develop testable hypotheses for laboratory and/or clinical validations.
Identification of Synthetic Lethal Interactions for Cancer Therapy
Identification of synthetic lethal (SL) interactions in human disease like cancer has a great potential to improve targeted therapies by targeting only genes having SL interactions with those mutated genes. Improved high-throughput technologies for drug and genetic screens enable genome-wide screen for genes sensitizing drugs. However, testing all possible combinations of hundreds of cell lines and thousands of compounds is infeasible and unaffordable in the foreseen future. Therefore, development of high performance classifiers that can effectively predict which genes sensitize which drugs for a given cell line will significantly reduce the number of experiments and thus greatly shorten the cycle of developing effective therapeutics.
Das SK, Sharma NK, Zhang B. Integrative network analysis reveals different pathophysiological mechanisms of insulin resistance among Caucasians and African Americans. BMC medical genomics 2015; 8(1).
GTEx Consortium . Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science (New York, N.Y.) 2015 May; 348(6235).
Jiang P, Scarpa JR, Fitzpatrick K, Losic B, Gao VD, Hao K, Summa KC, Yang HS, Zhang B, Allada R, Vitaterna MH, Turek FW, Kasarskis A. A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders. Cell reports 2015 May; 11(5).
Huan T, Rong J, Tanriverdi K, Meng Q, Bhattacharya A, McManus DD, Joehanes R, Assimes TL, McPherson R, Samani NJ, Erdmann J, Schunkert H, Courchesne P, Munson PJ, Johnson AD, O'Donnell CJ, Zhang B, Larson MG, Freedman JE, Levy D, Yang X. Dissecting the roles of microRNAs in coronary heart disease via integrative genomic analyses. Arteriosclerosis, thrombosis, and vascular biology 2015 Apr; 35(4).
Meng F, Speyer CL, Zhang B, Zhao Y, Chen W, Gorski DH, Miller FR, Wu G. PDGFRα and β play critical roles in mediating Foxq1-driven breast cancer stemness and chemoresistance. Cancer research 2015 Feb; 75(3).
Huan T, Meng Q, Saleh MA, Norlander AE, Joehanes R, Zhu J, Chen BH, Zhang B, Johnson AD, Ying S, Courchesne P, Raghavachari N, Wang R, Liu P, O'Donnell CJ, Vasan R, Munson PJ, Madhur MS, Harrison DG, Yang X, Levy D. Integrative network analysis reveals molecular mechanisms of blood pressure regulation. Molecular systems biology 2015 Jan; 11(1).
Maze I, Shen L, Zhang B, Garcia BA, Shao N, Mitchell A, Sun H, Akbarian S, Allis CD, Nestler EJ. Analytical tools and current challenges in the modern era of neuroepigenomics. Nature neuroscience 2014 Nov; 17(11).
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.
Mäkinen VP, Civelek M, Meng Q, Zhang B, Zhu J, Levian C, Huan T, Segrè AV, Ghosh S, Vivar J, Nikpay M, Stewart AF, Nelson CP, Willenborg C, Erdmann J, Blakenberg S, O'Donnell CJ, März W, Laaksonen R, Epstein SE, Kathiresan S, Shah SH, Hazen SL, Reilly MP, Lusis AJ, Samani NJ, Schunkert H, Quertermous T, McPherson R, Yang X, Assimes TL. Integrative genomics reveals novel molecular pathways and gene networks for coronary artery disease. PLoS genetics 2014 Jul; 10(7).
Bunyavanich S, Schadt EE, Himes BE, Lasky-Su J, Qiu W, Lazarus R, Ziniti JP, Cohain A, Linderman M, Torgerson DG, Eng CS, Pino-Yanes M, Padhukasahasram B, Yang JJ, Mathias RA, Beaty TH, Li X, Graves P, Romieu I, Navarro Bd, Salam MT, Vora H, Nicolae DL, Ober C, Martinez FD, Bleecker ER, Meyers DA, Gauderman WJ, Gilliland F, Burchard EG, Barnes KC, Williams LK, London SJ, Zhang B, Raby BA, Weiss ST. Integrated genome-wide association, coexpression network, and expression single nucleotide polymorphism analysis identifies novel pathway in allergic rhinitis. BMC medical genomics 2014; 7.
Brennand K, Savas JN, Kim Y, Tran N, Simone A, Hashimoto-Torii K, Beaumont KG, Kim HJ, Topol A, Ladran I, Abdelrahim M, Matikainen-Ankney B, Chao SH, Mrksich M, Rakic P, Fang G, Zhang B, Yates JR, Gage FH. Phenotypic differences in hiPSC NPCs derived from patients with schizophrenia. Molecular psychiatry 2015 Mar; 20(3).
Skinner MK, Savenkova MI, Zhang B, Gore AC, Crews D. Gene bionetworks involved in the epigenetic transgenerational inheritance of altered mate preference: environmental epigenetics and evolutionary biology. BMC genomics 2014; 15.
Zhang B, Gaiteri C, Bodea LG, Wang Z, McElwee J, Podtelezhnikov AA, Zhang C, Xie T, Tran L, Dobrin R, Fluder E, Clurman B, Melquist S, Narayanan M, Suver C, Shah H, Mahajan M, Gillis T, Mysore J, Macdonald ME, Lamb JR, Bennett DA, Molony C, Stone DJ, Gudnason V, Myers AJ, Schadt EE, Neumann H, Zhu J, Emilsson V. Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer's Disease. Cell 2013 Apr; 153(3).
Ding Y, Hubert CG, Herman J, Corrin P, Toledo CM, Skutt-Kakaria K, Vazquez J, Basom R, Zhang B, Risler JK, Pollard SM, Nam DH, Delrow JJ, Zhu J, Lee J, DeLuca J, Olson JM, Paddison PJ. Cancer-Specific requirement for BUB1B/BUBR1 in human brain tumor isolates and genetically transformed cells. Cancer discovery 2013 Feb; 3(2).
Lee JM, Galkina EI, Levantovsky RM, Fossale E, Anne Anderson M, Gillis T, Srinidhi Mysore J, Coser KR, Shioda T, Zhang B, Furia MD, Derry J, Kohane IS, Seong IS, Wheeler VC, Gusella JF, Macdonald ME. Dominant effects of the Huntington's disease HTT CAG repeat length are captured in gene-expression data sets by a continuous analysis mathematical modeling strategy. Human molecular genetics 2013 Apr;.
Huan T, Zhang B, Wang Z, Joehanes R, Zhu J, Johnson AD, Ying S, Munson PJ, Raghavachari N, Wang R, Liu P, Courchesne P, Hwang SJ, Assimes TL, McPherson R, Samani NJ, Schunkert H, Meng Q, Suver C, O'Donnell CJ, Derry J, Yang X, Levy D. A systems biology framework identifies molecular underpinnings of coronary heart disease. Arteriosclerosis, thrombosis, and vascular biology 2013 Jun; 33(6).
He X, Fuller CK, Song Y, Meng Q, Zhang B, Yang X, Li H. Sherlock: Detecting Gene-Disease Associations by Matching Patterns of Expression QTL and GWAS. American journal of human genetics 2013 May; 92(5).
Wang IM, Zhang B, Yang X, Zhu J, Stepaniants S, Zhang C, Meng Q, Peters M, He Y, Ni C, Slipetz D, Crackower MA, Houshyar H, Tan CM, Asante-Appiah E, O'Neill G, Luo MJ, Thieringer R, Yuan J, Chiu CS, Lum PY, Lamb J, Boie Y, Wilkinson HA, Schadt EE, Dai H, Roberts C. Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers. Molecular systems biology 2012; 8.
Skinner MK, Mohan M, Haque MM, Zhang B, Savenkova MI. Epigenetic transgenerational inheritance of somatic transcriptomes and epigenetic control regions. Genome biology 2012 Oct; 13(10).
Jostins L, Ripke S, Weersma RK, Duerr RH, McGovern DP, Hui KY, Lee JC, Schumm LP, Sharma Y, Anderson CA, Essers J, Mitrovic M, Ning K, Cleynen I, Theatre E, Spain SL, Raychaudhuri S, Goyette P, Wei Z, Abraham C, Achkar JP, Ahmad T, Amininejad L, Ananthakrishnan AN, Andersen V, Andrews JM, Baidoo L, Balschun T, Bampton PA, Bitton A, Boucher G, Brand S, Büning C, Cohain A, Cichon S, D'Amato M, De Jong D, Devaney KL, Dubinsky M, Edwards C, Ellinghaus D, Ferguson LR, Franchimont D, Fransen K, Gearry R, Georges M, Gieger C, Glas J, Haritunians T, Hart A, Hawkey C, Hedl M, Hu X, Karlsen TH, Kupcinskas L, Kugathasan S, Latiano A, Laukens D, Lawrance IC, Lees CW, Louis E, Mahy G, Mansfield J, Morgan AR, Mowat C, Newman W, Palmieri O, Ponsioen CY, Potocnik U, Prescott NJ, Regueiro M, Rotter JI, Russell RK, Sanderson JD, Sans M, Satsangi J, Schreiber S, Simms LA, Sventoraityte J, Targan SR, Taylor KD, Tremelling M, Verspaget HW, De Vos M, Wijmenga C, Wilson DC, Winkelmann J, Xavier RJ, Zeissig S, Zhang B, Zhang CK, Zhao H, Silverberg MS, Annese V, Hakonarson H, Brant SR, Radford-Smith G, Mathew CG, Rioux JD, Schadt EE, Daly MJ, Franke A, Parkes M, Vermeire S, Barrett JC, Cho JH. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012 Nov; 491(7422).
Tran LM, Zhang B, Zhang Z, Zhang C, Xie T, Lamb JR, Dai H, Schadt EE, Zhu J. Inferring causal genomic alterations in breast cancer using gene expression data. BMC systems biology 2011; 5.
Greenawalt DM, Dobrin R, Chudin E, Hatoum IJ, Suver C, Beaulaurier J, Zhang B, Castro V, Zhu J, Lum PY, Schadt EE, Kaplan LM. A survey of the genetics of stomach, liver, and adipose gene expression from a morbidly obese cohort. Genome research 2011 Jul; 21(7).
Fraser HB, Babak T, Tsang J, Zhou Y, Zhang B, Mehrabian M, Schadt EE, He A, Truong A, Patel S, Nelson SF, Horvath S, Berliner JA, Kirchgessner TG, Lusis AJ, Lum PY, Schadt EE, Kaplan LM. Systematic detection of polygenic cis-regulatory evolution. PLoS genetics 2011 Mar; 7(3).
Zhang H, Meng F, Liu G, Zhang B, Zhu J, Wu F, Ethier SP, Miller F, Wu G, Patel S, Nelson SF, Horvath S, Berliner JA, Kirchgessner TG, Lusis AJ. Forkhead transcription factor foxq1 promotes epithelial-mesenchymal transition and breast cancer metastasis. Cancer research 2011 Feb; 71(4).
Pandey G, Zhang B, Chang AN, Myers CL, Zhu J, Kumar V, Schadt EE, Miller F, Wu G. An integrative multi-network and multi-classifier approach to predict genetic interactions. PLoS computational biology 2010; 6(9).
Yang X, Zhang B, Molony C, Chudin E, Hao K, Zhu J, Gaedigk A, Suver C, Zhong H, Leeder JS, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich RG, Slatter JG, Schadt EE, Kasarskis A, Lum PY. Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver. Genome research 2010 Aug; 20(8).
Millstein J, Zhang B, Zhu J, Schadt EE, Hao K, Zhu J, Gaedigk A, Suver C, Zhong H, Leeder JS, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich RG, Slatter JG, Schadt EE, Kasarskis A, Lum PY. Disentangling molecular relationships with a causal inference test. BMC genetics 2009; 10.
Zhang B, Srihari S. Fast k-nearest Neighbor Classification Using Cluster-based Trees. IEEE Transaction Pattern Analysis and Machine Intelligence 2004; 26(4).
Schadt EE, Zhang B, Zhu J, Schadt EE. Advances in systems biology are enhancing our understanding of disease and moving us closer to novel disease treatments. Genetica 2009 Jun; 136(2).
Zhu J, Zhang B, Schadt EE. A systems biology approach to drug discovery. Advances in genetics 2008; 60.
Zhu J, Zhang B, Smith EN. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nature genetics 2008 Jul; 40(7).
Emilsson V, Thorleifsson G, Zhang B, Leonardson AS, Zink F, Zhu J, Carlson S, Helgason A, Stefansson H, Fossdal R, Kristjansson K, Gislason HG, Stefansson T, Leifsson BG, Thorsteinsdottir U, Lamb JR, Gulcher JR, Reitman ML, Kong A, Schadt EE, Stefansson K. Genetics of gene expression and its effect on disease. Nature 2008 Mar; 452(7186).
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, Stefansson H, Fossdal R, Kristjansson K, Gislason HG, Stefansson T, Leifsson BG, Thorsteinsdottir U, Lamb JR, Gulcher JR, Reitman ML, Kong A, Schadt EE, Stefansson K. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar; 452(7186).
Langfelder P, Zhang B, Horvath S, 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. Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R. Bioinformatics (Oxford, England) 2008 Mar; 24(5).
Horvath S, Zhang B, Carlson M, Febbo PG, Kornblum HI, Cloughesy TF, Nelson SF, Mischel PS. Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target. Proceedings of the National Academy of Sciences of the United States of America 2006 Nov; 103(46).
Gargalovic PS, Imura M, Zhang B, Gharavi NM, Clark MJ, Pagnon J, Yang WP, He A, Truong A, Patel S, Nelson SF, Horvath S, Berliner JA, Kirchgessner TG, Lusis AJ, Febbo PG, Kornblum HI, Cloughesy TF, Nelson SF, Mischel PS. Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids. Proceedings of the National Academy of Sciences of the United States of America 2006 Aug; 103(34).
Ghazalpour A, Doss S, Zhang B, Wang S, Plaisier C, Castellanos R, Brozell A, Schadt EE, Drake TA, Lusis AJ, Horvath S, Horvath S, Berliner JA, Kirchgessner TG, Lusis AJ. Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS genetics 2006 Aug; 2(8).
Carlson MR, Zhang B, Fang Z, Mischel PS, Horvath S, Nelson SF, Brozell A, Schadt EE, Drake TA, Lusis AJ, Horvath S. Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks. BMC genomics 2006; 7.
Zhang B, Horvath S, Fang Z, Mischel PS, Horvath S, Nelson SF. A general framework for weighted gene co-expression network analysis. Statistical applications in genetics and molecular biology 2005; 4.
Zhang B, Horvath S. Ridge regression based hybrid genetic algorithms for multi-locus quantitative trait mapping. International journal of bioinformatics research and applications 2005; 1(3).
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.Zhang 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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