Michael Zhang

Cecil H. and Ida Green Distinguished Chair of Systems Biology Science
Professor - Biological Sciences
 
972-883-2523
RL4748
Tags: Biology Genomics, Systems and Computational Biology

Professional Preparation

Ph.D. - Statistical Physics
Rutgers University - 1987
B.S. - Mechanical Engineering
University of Science and Technology of China - 1981

Research Areas

Research Interests
The long-term goal of research in our lab is to use mathematical and statistical methods to identify functional elements in eucaryotic genomes, especially the genes and their control and regulatory elements. A genome is the program book of a life, genome research will lead to eventual decoding of the entire genetic language of life and its grammar. Driven by the Human Genome Project, our current interest is on two related problems: genome/chromatin organization and gene regulation networks. At the transcriptional level, identification of cis-elements (both genetic and epigenetic) is the key focus. We are increasingly interested post-transcriptional regulations, especially at splicing regulation and translational regulation. Constitutive coding exons are relatively easy to identify, the greatest challenge lies in the identification of end exons and alternatively spliced exons that are often tissue- and developmental specific. Since this requires the study of many important control and regulatory elements for gene expression, this link between gene structure and function at the genomic or pre-/pri- RNA level requires high-throughput functional studies. Detecting cis regulatory elements and modeling gene expression networks are difficult challenges in the functional genomics era. Working closely with bench-scientists, our investigation will undoubtedly contribute to the understanding of genome organization as well as gene expression and regulation mechanisms, which will in turn have a profound impact on biology and medicine.

Publications

Wu J, Akerman M, Sun S, McCombie WR, Krainer AR, Zhang MQ. SpliceTrap: a method to quantify alternative splicing under single cellular conditions. Bioinformatics. 2011 Nov 1;27(21):3010-6. Epub 2011 Sep 6. PubMed PMID: 21896509; PubMed Central PMCID: PMC3198574. 2011 - Publication
Yang S, Yalamanchili HK, Li X, Yao KM, Sham PC, Zhang MQ, Wang J. Correlated evolution of transcription factors and their binding sites. Bioinformatics. 2011 Nov 1;27(21):2972-8. Epub 2011 Sep 6. PubMed PMID: 21896508. 2011 - Publication
Zhirui Hu, Minping Qian and Michael Q. Zhang. Novel Markov model of induced pluripotency predicts gene expression changes in reprogramming. BMC Systems Biology, 2011. 2011 - Publication
Bernard D, Prasanth KV, Tripathi V, Colasse S, Nakamura T, Xuan Z, Zhang MQ , Sedel F, Jourdren L, Coulpier F, Triller A, Spector DL, Bessis A (2010) “ A long nuclear -retained non-coding RNA regulates synaptogenesis by modulating gene expression. ”EMBO J, 29:3082-93. 2010 - Publication
Wang SM, Zhang MQ. (2010) “Transcriptome study for early hematopoiesis - achievement, challenge and new opportunity.” J Cell Physiol 223(3):549-52. 2010 - Publication
Kinney JB, Murugan A, Callan CG Jr, Cox EC. (2010) “Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence.” PNAS May 3. [Epub ahead of print]                                         2010 - Publication
Wang SM, Zhang MQ. (2010) “Transcriptome study for early hematopoiesis - achievement, challenge and new opportunity.” J Cell Physiol 223(3):549-52. 2010 - Publication
Mitra R, Bandyopadhyay S, Maulik U, Zhang MQ . (2010) “ SFSSClass: an integrated approach for miRNA based tumor classification.BMC Bioinformatics. ” 2010 Jan 18;11 Suppl 1:S22.   2010 - Publication
Chicas A, Wang X, Zhang C, McCurrach M, Zhao Z, Mert O, Dickins RA, Narita M, Zhang M, Lowe SW. (2010) “Dissecting the unique role of the retinoblastoma tumor suppressor during cellular senescence.” Cancer Cell 17(4):376-87. 2010 - Publication
Harris RA, Wang T, Coarfa C, Nagarajan RP, Hong C, Downey SL, Johnson BE, Fouse SD, Delaney A, Zhao Y, Olshen A, Ballinger T, Zhou X, Forsberg KJ, Gu J, Echipare L, O'Geen H, Lister R, Pelizzola M, Xi Y, Epstein CB, Bernstein BE, Hawkins RD, Ren B, Chung WY, Gu H, Bock C, Gnirke A, Zhang MQ , Haussler D, Ecker JR, Li W, Farnham PJ, Waterland RA, Meissner A, Marra MA, Hirst M, Milosavljevic A, Costello JF. (2010) 2010 - Publication

Appointments

Cecil H. and Ida Green Distinguished Chair Professor in Systems Biology
UT Dallas [2009–2020]

Additional Information

Molecular Biology and Bioinformatics Training
  • Life Technology Training Center, Recombinant DNA Techniques I and II, (Lab.Course Certificate), Mar. and Sept., 1992.
  • SIAM Computational Biology Workshop (Training Certificate), Rutgers University, Aug., 1992.
  • Advanced Automated/Diagnostic DNA Sequencing Workshop, Baylor College of Medicine, Jun., 1993.
  • Molecular Genetics, Cell Biology and Cell Cycle of Fission Yeast Course, CSHL, Nov., 1993.
  • Experimenting on Differential Display (Liang and Pardee,1992) Method by Internal Dye-labeling in David Beach's Lab., 5 months,1994.
  • Advanced Genome Sequence Analysis Course, CSHL, Mar., 1995.
  • Nucleic Acid & Protein Sequence Analysis Workshop, Pittsburgh Supercomputing Center, Jun. 1995.
  • Unix (Solaris 2.5x) system administration certificate from Sun microsystems, 1997.
 

News Articles

Scientists Advance Understanding of DNA Responsible for Diseases
Researchers from the School of Natural Sciences and Mathematics at The University of Texas at Dallas have teamed with colleagues at the UT Southwestern Children’s Medical Center Research Institute to create a new method for understanding the causes of genetic diseases, such as sickle cell anemia and some cancers. 

The new system allows researchers to define the molecular structures that control the activity of regulatory DNA sequences in the human genome. 

Dr. Michael Q. Zhang and postdoctoral researcher Dr. Yong Chen from Zhang’s Computational Biology Laboratory — along with assistant professor of biological sciences Dr. Zhenyu Xuan — collaborated on the formulation of the system called CAPTURE, or CRISPR Affinity Purification in situ of Regulatory Elements. Their work was published in a recent issue of the journal Cell. 
Scientist Flourishes in Eugene McDermott Graduate Fellows Program
Doctoral student Peng Xie came to The University of Texas at Dallas primarily to follow his mentor, Dr. Michael Q. Zhang, and his passion, computational biology.

In the three years he has been on campus, Xie has exemplified the multitude of reasons that promising graduate students come to UT Dallas — opportunity, support and career advancement.

Xie is a member of the first cohort of the Eugene McDermott Graduate Fellows Program. In addition to a stipend, tuition and fees, and a research budget, the McDermott fellowship provides professional development and enrichment opportunities.
Scientist Strengthens Systems Biology Initiative
Dr. Michael Zhang, a leading scientist in computational biology and genomic research, has joined UT Dallas as professor and Cecil H. and Ida Green Distinguished Chair of Systems Biology Science. Zhang’s chaired position in the School of Natural Sciences and Mathematics begins establishment of a new Center for Systems Biology. “In attracting a researcher of the stature of Dr. Zhang to our faculty, we expect to nucleate a major effort in genomics and computational biology that focuses on the genetic underpinnings of disease,” said Myron Salamon, dean of the School of Natural Sciences and Mathematics. Computational biology bridges the life sciences and quantitative sciences – mathematics, statistics and computer science – to understand living systems.

Affiliations

Posdoctoral Fellow
2020/10–2020/01
Courant Institute of Mathematics, NYU
JuniorFellow/Assistant/Associate/Full Professor/AdjunctFaculty
2020/01–2013/12
Cold Spring Harbor Laboratory and Watson School of Biological Sciences
Adjunct Faculty
2020/01–2010/12
Genetics/Physics/Math,  SUNY / Stony Brook University
Adjunct Faculty
2020/07
School of Informatics Sciences/School of Medicine, Tsinghua University