Ph.D. - Statistical Physics
Rutgers University - 1987
B.S. - Mechanical Engineering
University of Science and Technology of China - 1981
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.
Zhang C, Zhang MQ. (2007) Biomedical literature mining. Chap 10. in Introduction to Bioinformatics: A workbook approach. Mathura V ed. Elsevier. In press. 2007 - Publication
Kim YC, Jung Y-C, Xuan Z, Tong H, Zhang MQ, Wang SM (2006) Pan-genome isolation of low abundant transcripts through SAGE. FEBS Lett 580:6721-6729. 2007 - Publication
Murchison EP, Stein P, Xuan Z, Pan H, Zhang MQ, Schultz RM, Hannon GJ (2007) Critical roles for Dicer in the female germine. Gene & Dev. 21:682-93. 2007 - Publication
Zhang C, Krainer AR, Zhang MQ. (2007) Evolutionary impact of limited splicing fidelity in mammalian genes. . 23:484-8. 2007 - Publication
Jiang C, Xuan Z, Zhao F, Zhang MQ (2007) TRED: A Transcriptional Regulatory Element Database, new entries and other development. Nucleic Acid Res 35: D137-D140 2007 - Publication
Smith AD, Sumazin P and Zhang MQ (2007) Tissue-specific regulatory elements in mammalian promoters. Mol Sys Biol. 3:73. 2007 - Publication
Smith PJ, Zhang C, Wang J, Chew SL, Zhang MQ, Krainer AR (2006) An increased specificity score matrix for the prediction of SF2/ASF-specific exonix splicing enhancers. Hum Mol Genet 15(16):2490-2508. 2007 - Publication
Das D, Nahle Z, Zhang MQ (2006) Adaptively Inferring Human Transcriptional Subnetworks. Mol Sys Biol. 2:2006.0029. 2006 - Publication
Fang F, Fan SC, Zhang X and Zhang MQ (2006) Predicting Methylation Status of CpG Islands in the Human Brain. Bioinformatics, 22:2204-2209. 2006 - Publication
Benita Y, Oosting RS, Xuan Z, Wise MJ, Zhang QM, Humphery-Smith I (2006). Challenges in the prediction of small genes in the human genome. In preparation*. Review. 2006 - Publication
Cecil H. and Ida Green Distinguished Chair Professor in Systems Biology
UT Dallas [2009–2020]
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.
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.
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.
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.
Courant Institute of Mathematics, NYU
Cold Spring Harbor Laboratory and Watson School of Biological Sciences
Genetics/Physics/Math, SUNY / Stony Brook University
School of Informatics Sciences/School of Medicine, Tsinghua University