Schaffer JD, Dimitrova N, Zhang MQ (2006) Bioinformatics. Chap. 26 in Advances in Healthcare Technology: Shaping the Future of Medical Care. Spekowius G & Wendler T eds. Pp421-438. Springer. 2007 - Publication
He L, He X, Lim LP, de Stanchina E, Xuan Z, Liang Y, Xue W, Zender L, Magnus J, Ridzon D, Jackson AL, Linsley PS, Chen C, Lowe SW, Cleary MA, Hannon GJ (2007) A microRNA component of the p53 tumour suppressor network. Nature. 447, 1130-4. 2007 - Publication
Martinez MJ, Smith AD, Li B, Zhang MQ, Harrod KS. (2007) Computational prediction of novel components of lung transcriptional networks. Bioinformatics. 23:21-29. 2007 - Publication
Karginov FV, Conaco C, Xuan Z, Schmidt BH, Parker JS, Mandel G, Hannon GJ. (2007) A biochemical approach to identifying microRNA targets. Proc Natl Acad Sci U S A. 104:19291-6. 2007 - Publication
Zhao X, Leotta A, Kustanovich V, Lajonchere C, Geschwind DH, Law K, Law P, Qiu S, Lord C, Sebat J, Ye K, Wigler M. (2007) A unified genetic theory for sporadic and inherited autism. Proc Natl Acad Sci U S A. 104:12831-6. 2007 - Publication
Schones DE, Smith AD and Zhang MQ (2007) Statistical significance of cis-regulatory modules. BMC Bioinformatics 8:19. 2007 - Publication
Kim TH, Abdullaev Z, Smith AD, Ching KA, Loukinow D, Green RD, Zhang MQ, Lobanenkov V, Ren B (2007) Analysis of the vertebrate insulator protein CTCF binding sites in the human genome. Cell 128(6):1231-45. 2007 - Publication
Zhang MQ (2007) Inferring Gene Regulatory Networks - Chapter 21 in: Bioinformatics - From Genomes to Therapies (T. Lengauer, ed.) Wiley-VCH. p807-828. 2007 - Publication
Zhang C, Hastings ML Krainer AR, Zhang MQ. (2007) Dual-specificity splice sites function alternatively as 5' and 3' splice sites. Proc. Natl. Acad. Sci. USA 104, 15028-15033. 2007 - Publication
Mignone JL, Roig-Lopez JL, Fedtsova N, Schones DE, Manganas LN, Maletic-Savatic M, Keyes WM, Mills AA, Gleiberman A, Zhang MQ, Enikolopov G. (2007) Neural Potential of a Stem Cell Population in the Hair Follicle. Cell Cycle 6:2161-70. 2007 - Publication
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.