Jianrong Wang

Jianrong Wang

Assistant Professor, Department of Computational Mathematics, Science & Engineering;
Room 2507J, Engineering Building
  428 S. Shaw Ln.
 (517) 432-0370
  wangj164@msu.edu

Assistant Professor, 2017, Michigan State University
Postdoctoral Associate, 2016, Stanford University
Postdoctoral Associate, 2012-2016, Massachusetts Institute of Technology and Broad Institute
Ph.D., 2012, Bioinformatics, Georgia Institute of Technology
B.S., 2007, Control Science and Engineering, Tsinghua University

 

Jianrong Wang’s interdisciplinary research is in the fields of bioinformatics, machine learning, gene regulation and systems biology, with a focus on developing novel statistical models and machine learning algorithms to infer large-scale context-dependent gene regulatory networks and their association with complex phenotypes by integrating heterogeneous high-dimensional datasets.

Jianrong is also actively collaborating with experimental experts in genetics, development biology, plant biology, epigenomics and proteomics, using diverse model species (mouse, drosophila, sheep and plants) for data generation and integration. The efficient interactions between experiments and computation facilitate the transformative capacity of our innovative methodology development, leading to deeper biological insights and systems-level understandings.

Four major computational biology research topics include:

• Probabilistic modeling of long-range three-dimensional enhancer-gene networks in diverse cellular-contexts and inference of hierarchical regulatory logic of combinatorial transcription factors on gene expression.

• Network-based prediction and functional annotation of non-coding genetic variants associated with complex phenotypes in different species.

• Machine learning algorithms to predict regulatory elements of gene expression (insulators, enhancers and boundary elements), large-scale chromatin domains, and histone modification signatures (‘histone-code’) based on genomics, epigenomics and transcriptomics data.

 • Statistical and computational methodology development for efficient design, analysis and interpretation of biological big-data generated from new high-throughput techniques.

 

[1] Eugenio Marco, Wouter Meuleman, Jialiang Huang, Kimberly Glass, Luca Pinello, Jianrong Wang, Manolis Kellis and Guo-Cheng Yuan. Multi-scale chromatin state annotation using a hierarchical hidden Markov model. 2017 Nature Communications 8:15011.

[2] Jianrong Wang, Cristina Vicente-Garcia, Davide Seruggia, Eduardo Molto, Ana Fernandez-Minan, Ana Neto, Elbert Lee, Jose Luis Gomez-Skarmeta, Lluis Montoliu, Victoria V. Lunyak and I. King Jordan. MIR retrotransposon sequences provide insulators to the human genome. 2015 Proc Natl Acad Sci USA 112(32):E4428-4437.

[3] Roadmap Epigenomics Consortium et al. Integrative analysis of 111 reference human epigenomes. 2015 Nature 518:317-330. (Integrative Analysis Lead Author)

[4] Jianrong Wang, Victoria V. Lunyak and I. King Jordan. Chromatin signature discovery via histone modification profile alignments. 2012 Nucleic Acids Research 40(21):10642-10656. 

[5] Jianrong Wang, Victoria V. Lunyak and I. King Jordan. Genome-wide prediction and analysis of human chromatin boundary elements. 2012 Nucleic Acids Research 40(2):511-529, (Cover Story). 

If you are interested, please send an email to Dr. Wang (wangj164@msu.edu) with your application materials.

FS-2019: CMSE-201, “Introduction to Computational Modeling”. 
SS-2019: CMSE-801, “Introduction to Computational Modeling”.
FS-2018: CMSE-491/CMSE-890, “Computational Medicine”, New course on bioinformatics, systems biology, computational genomics, multi-omics integration and genotype-phenotype mapping, including algorithm lectures, interactive journal clubs, and real-world projects.
SS-2018: CMSE-201, “Introduction to Computational Modeling”.
Summer 2017: Computational Biology 3-week Workshop Series: Interactive workshop on bioinformatics and its applications for students with diverse backgrounds, including real-world data processing, programming, statistical analysis and visualizations.
SS-2017: Modular course material development for “Computational biology: programming, statistics and RNA-seq analysis”.

Click "Teaching" link to see past courses.

2019.05: NRT-IMPACTS fellowships to Ph.D. student Hao Wang.
2019.04: Master student Hongjie Ke successfully get admitted to the Ph.D. program of statistics in the University of Maryland.
2019.03: Ph.D. student Hao Wang get Honorable Mention for Fitch H. Beach Award (Top one of CMSE Dept.).
2019.02: Undergraduate research assistant Junyi Bao successfully get admitted to the master program of statistics in Cornell University.
2019.01: NRT-IMPACTS fellowships to Ph.D. students Binbin Huang and Hao Wang.
2018.12: Undergraduate research assistant Linghao Song successfully get admitted to the master program of bioinformatics in the University of Chicago.
2018.05: Ph.D. student Binbin Huang get BEACON fellowship.
2018.03: Ph.D. student Hao Wang get First Place for DewGood Award for Public Service (Top one of College of Engineering).
2018.03: Ph.D. student Hao Wang get Outstanding Poster Award in Interdisciplinary Areas.