Zichen Wang, PhD
- ASSISTANT PROFESSOR | Pharmacological Sciences
Research Topics:Aging, Bioinformatics, Biomedical Informatics, Computational Biology, Gene Expressions, Genomics, Neural Networks, Systems Biology, Systems Pharmacology, Translational Research
Dr. Wang is a Research Assistant Professor in the Ma'ayan Laboratory and the Mount Sinai Center for Bioinformatics. His research focuses on developing compuatational and machine learning methods and software applications to investigate biomedical big data including high-throughput omics profiling and clinical data such as electronic medical records (EMR).
BS, China Agricultural University
PhD, Icahn School of Medicine at Mount Sinai
Postdoctoral Fellowship, Icahn School of Medicine at Mount Sinai
My research in this area primarily harnessed the molecular high-throughput data from drug treatment to systematically investigate the mechanism of action (MOA) for drugs.
- Developed a multilabel classification approach to predict adverse drug reactions (ADRs) by utilizing the large-scale drug-induced gene expression profiles from the LINCS L1000 data and chemical structures. Article describing this approach is published in Bioinformatics. PMID: 27153606
A companion website visualizing the predicted ADRs for drugs is available at : http://maayanlab.net/SEP-L1000/
- Developed a graph-based dimensionality reduction algorithm to visualize tens of thousands drug-induced transcriptomics signatures. This approach facilitates the discovery of drug MOAs. It has been applied to transcriptomics datasets:
- LINCS Joint Project (LJP): 2,300 expression signatures from six breast cancer cell lines treated with ~100 single molecule perturbations. An article describing this study has been published in Nature Communications. PMID: 29084964
- L1000 Firework Display (L1000FWD): over 16,000 drug-induced gene expression signatures from the LINCS L1000 dataset. An article describing this study has been published in Bioinformatics. PMID: 29420694
Translational Biomedical Informatics
I also focus on developing methods to mine the data from the Electronic Medical Records (EMR) to extract human phenotypes such as physiological health status and complex diseases. In our recent study (PMID: 29113935), we developed a deep learning regression model to estimate physiological age for over 300,000 patients using routine laboratory tests and vital signs. This approach discovered that there are patients with improved and decreased health status with regard to their age.
Bioinformatics Resources, Tools and Pipelines for Data Integration
I have developed resources and tools for re-analysis of public datasets and integrating knowledge extracted from across various resources for biomedical research.
- CRowd Extracted Expression of Differential Signatures (CREEDS): a crowdsourcing approach to curate gene expression datasets from the NCBI's Gene Expression Omnibus (GEO) repository. An article describing the method and resultant resource has been published in Nature Communications. PMID: 27667448.
- Enrichr: a gene set enrichment analysis tool that includes one of the largest collections of annotated gene sets.
- Harmonizome: an encyclopedia for genes and proteins that integrates curated knowledge and high quality experimental data. An article describing this resource has been published in Database. PMID: 27374120
- An open and reproducible RNA-seq analysis pipeline: this pipeline is able to automatically process RNA-seq data from scratch and generate comprehensive and interactive report. An article describing this pipeline has been published in F1000Research. PMID: 27583132
Wang Z, Lachmann A, Keenan AB, Ma'ayan A, Stegle O. L1000FWD: Fireworks visualization of drug-induced transcriptomic signatures. Bioinformatics (Oxford, England) 2018 Feb;.
Wang Z, Li L, Glicksberg BS, Israel A, Dudley JT, Ma'ayan A. Predicting Age by Mining Electronic Medical Records with Deep Learning Characterizes Differences between Chronological and Physiological Age. Journal of biomedical informatics 2017 Nov;.
Fu J, Wang Z, Lee K, Wei C, Liu Z, Zhang M, Zhou M, Cai M, Zhang W, Chuang PY, Ma'ayan A, He JC, Liu Z. Transcriptomic analysis uncovers novel synergistic mechanisms in combination therapy for lupus nephritis. Kidney international 2017 Nov;.
Asada N, Kunisaki Y, Pierce H, Wang Z, Fernandez NF, Birbrair A, Ma'ayan A, Frenette PS. Differential cytokine contributions of perivascular haematopoietic stem cell niches. Nature cell biology 2017 Mar; 19(3).
von Schimmelmann M, Feinberg PA, Sullivan JM, Ku SM, Badimon A, Duff MK, Wang Z, Lachmann A, Dewell S, Ma'ayan A, Han MH, Tarakhovsky A, Schaefer A. Polycomb repressive complex 2 (PRC2) silences genes responsible for neurodegeneration. Nature neuroscience 2016 Oct; 19(10).
Niepel M, Hafner M, Duan Q, Wang Z, Paull EO, Chung M, Lu X, Stuart JM, Golub TR, Subramanian A, Ma'ayan A, Sorger PK. Common and cell-type specific responses to anti-cancer drugs revealed by high throughput transcript profiling. Nature communications 2017 Oct; 8(1).
Wang Z, Monteiro CD, Jagodnik KM, Fernandez NF, Gundersen GW, Rouillard AD, Jenkins SL, Feldmann AS, Hu KS, McDermott MG, Duan Q, Clark NR, Jones MR, Kou Y, Goff T, Woodland H, Amaral FM, Szeto GL, Fuchs O, Schüssler-Fiorenza Rose SM, Sharma S, Schwartz U, Bausela XB, Szymkiewicz M, Maroulis V, Salykin A, Barra CM, Kruth CD, Bongio NJ, Mathur V, Todoric RD, Rubin UE, Malatras A, Fulp CT, Galindo JA, Motiejunaite R, Jüschke C, Dishuck PC, Lahl K, Jafari M, Aibar S, Zaravinos A, Steenhuizen LH, Allison LR, Gamallo P, de Andres Segura F, Dae Devlin T, Pérez-García V, Ma'ayan A. Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd. Nature communications 2016 Sep; 7.
Pfau ML, Purushothaman I, Feng J, Golden SA, Aleyasin H, Lorsch ZS, Cates HM, Flanigan ME, Menard C, Heshmati M, Wang Z, Ma'ayan A, Shen L, Hodes GE, Russo SJ. Integrative Analysis of Sex-Specific microRNA Networks Following Stress in Mouse Nucleus Accumbens. Frontiers in molecular neuroscience 2016; 9.
Kong DS, Kim J, Lee IH, Kim ST, Seol HJ, Lee JI, Park WY, Ryu G, Wang Z, Ma'ayan A, Nam DH. Integrative radiogenomic analysis for multicentric radiophenotype in glioblastoma. Oncotarget 2016 Mar; 7(10).
Rezza A, Wang Z, Sennett R, Qiao W, Wang D, Heitman N, Mok KW, Clavel C, Yi R, Zandstra P, Ma'ayan A, Rendl M. Signaling Networks among Stem Cell Precursors, Transit-Amplifying Progenitors, and their Niche in Developing Hair Follicles. Cell reports 2016 Mar; 14(12).
Morgan DJ, Poolman TM, Williamson AJ, Wang Z, Clark NR, Ma'ayan A, Whetton AD, Brass A, Matthews LC, Ray DW. Glucocorticoid receptor isoforms direct distinct mitochondrial programs to regulate ATP production. Scientific reports 2016 May; 6.
Kuleshov MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z, Koplev S, Jenkins SL, Jagodnik KM, Lachmann A, McDermott MG, Monteiro CD, Gundersen GW, Ma'ayan A. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic acids research 2016 Jul; 44(W1).
Wang Z, Ma'ayan A. An open RNA-Seq data analysis pipeline tutorial with an example of reprocessing data from a recent Zika virus study. F1000Research 2016; 5.
Rouillard AD, Gundersen GW, Fernandez NF, Wang Z, Monteiro CD, McDermott MG, Ma'ayan A. The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins. Database : the journal of biological databases and curation 2016; 2016.
Rouillard AD, Wang Z, Ma'ayan A. Reprint of . Computational biology and chemistry 2015 Dec; 59 Pt B.
Wang Z, Clark NR, Ma'ayan A. Drug-induced adverse events prediction with the LINCS L1000 data. Bioinformatics (Oxford, England) 2016 Aug; 32(15).
Rouillard AD, Wang Z, Ma'ayan A. Publisher’s Note:Abstraction for data integration:Fusing mammalian molecular, cellular and phenotype big datasets for better knowledge extraction. Computational biology and chemistry 2015 Oct; 58.
Clark NR, Szymkiewicz M, Wang Z, Monteiro CD, Jones MR, Ma'ayan A. Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool. Proceedings. IEEE International Conference on Bioinformatics and Biomedicine 2015 Nov; 2015.
Wang Z, Clark NR, Ma'ayan A. Dynamics of the discovery process of protein-protein interactions from low content studies. BMC systems biology 2015 Jun; 9.
Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV, Clark NR, Ma'ayan A. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC bioinformatics 2013 Apr; 14.
Ma'ayan A, Rouillard AD, Clark NR, Wang Z, Duan Q, Kou Y. Lean Big Data integration in systems biology and systems pharmacology. Trends in pharmacological sciences 2014 Sep; 35(9).
Duarte LF, Young AR, Wang Z, Wu HA, Panda T, Kou Y, Kapoor A, Hasson D, Mills NR, Ma'ayan A, Narita M, Bernstein E. Histone H3.3 and its proteolytically processed form drive a cellular senescence programme. Nature communications 2014 Nov; 5.
Duan Q, Wang Z, Fernandez NF, Rouillard AD, Tan CM, Benes CH, Ma'ayan A. Drug/Cell-line Browser: interactive canvas visualization of cancer drug/cell-line viability assay datasets. Bioinformatics (Oxford, England) 2014 Nov; 30(22).
Sennett R, Wang Z, Rezza A, Grisanti L, Roitershtein N, Sicchio C, Mok KW, Heitman NJ, Clavel C, Ma'ayan A, Rendl M. An Integrated Transcriptome Atlas of Embryonic Hair Follicle Progenitors, Their Niche, and the Developing Skin. Developmental cell 2015 Sep; 34(5).
Yu Z, Zhou X, Wang W, Deng W, Fang J, Hu H, Wang Z, Li S, Cui L, Shen J, Zhai L, Peng S, Wong J, Dong S, Yuan Z, Ou G, Zhang X, Xu P, Lou J, Yang N, Chen P, Xu RM, Li G. Dynamic phosphorylation of CENP-A at Ser68 orchestrates its cell-cycle-dependent deposition at centromeres. Developmental cell 2015 Jan; 32(1).
Wang W, Wang L, Chen C, Xiong G, Tan XY, Yang KZ, Wang ZC, Zhou Y, Ye D, Chen LQ. Arabidopsis CSLD1 and CSLD4 are required for cellulose deposition and normal growth of pollen tubes. Journal of experimental botany 2011 Oct; 62(14).
Keenan AB, Jenkins SL, Jagodnik KM, Koplev S, He E, Torre D, Wang Z, Dohlman AB, Silverstein MC, Lachmann A, Kuleshov MV, Ma'ayan A, Stathias V, Terryn R, Cooper D, Forlin M, Koleti A, Vidovic D, Chung C, Schürer SC, Vasiliauskas J, Pilarczyk M, Shamsaei B, Fazel M, Ren Y, Niu W, Clark NA, White S, Mahi N, Zhang L, Kouril M, Reichard JF, Sivaganesan S, Medvedovic M, Meller J, Koch RJ, Birtwistle MR, Iyengar R, Sobie EA, Azeloglu EU, Kaye J, Osterloh J, Haston K, Kalra J, Finkbiener S, Li J, Milani P, Adam M, Escalante-Chong R, Sachs K, Lenail A, Ramamoorthy D, Fraenkel E, Daigle G, Hussain U, Coye A, Rothstein J, Sareen D, Ornelas L, Banuelos M, Mandefro B, Ho R, Svendsen CN, Lim RG, Stocksdale J, Casale MS, Thompson TG, Wu J, Thompson LM, Dardov V, Venkatraman V, Matlock A, Van Eyk JE, Jaffe JD, Papanastasiou M, Subramanian A, Golub TR, Erickson SD, Fallahi-Sichani M, Hafner M, Gray NS, Lin JR, Mills CE, Muhlich JL, Niepel M, Shamu CE, Williams EH, Wrobel D, Sorger PK, Heiser LM, Gray JW, Korkola JE, Mills GB, LaBarge M, Feiler HS, Dane MA, Bucher E, Nederlof M, Sudar D, Gross S, Kilburn DF, Smith R, Devlin K, Margolis R, Derr L, Lee A, Pillai A. The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations. Cell systems 2018 Jan; 6(1).
Hodos R, Zhang P, Lee HC, Duan Q, Wang Z, Clark NR, Ma'ayan A, Wang F, Kidd B, Hu J, Sontag D, Dudley J. Cell-specific prediction and application of drug-induced gene expression profiles. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 2018; 23.
Torre D, Krawczuk P, Jagodnik KM, Lachmann A, Wang Z, Wang L, Kuleshov MV, Ma'ayan A. Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses. Scientific data 2018 Feb; 5.