Zhang Z, Lin H, Zhang MQ, Ma B, Li M (2008) ZOOM! Zillions of Oligos Mapped. Bioinformatics, 24:2431-7. 2008 - Publication
Cuddapah S, Chen X, Xuan Z, Roh T-Y, Cui K, Smith AD, Byun JS, Zhang MQ, Fuller MT, Zhao K (2008) Identification of potential human polycomb response elements in T cells. Nat. Genet, revising. 2008 - Publication
Wang Z*, Zang C*, Rosenfeld J*, Schones DE, Barski A, Cuddapah S, Cui K, Roh T-Y, Peng W, Zhang MQ, Zhao K (2008) Genome-wide correlation analysis of histone acetylation and methylation in human T cells. Nat. Genet. (*equal contributing first author), Nat Genet, 40:897-903. 2008 - Publication
Smith AD, Xuan Z, Zhang MQ (2008) Using quality scores and longer reads improves accuracy of Solexa read mapping. BMC Bioinformatics, 9:128. 2008 - Publication
Barrera LO, Li Z, Smith AD, Arden KC, Cavenee WK, Zhang MQ, Green RD, Ren B (2008) Genome-wide mapping and analysis of active promoters in mouse embryonic stem cells and adult organs. Genome Res. 18:46-59. 2008 - Publication
Fan S, Zhang MQ, Zhang X (2008) Histone Methylation Marks Play Important Roles in Predicting the Methylation Status of CpG Islands. BBRC, 374:559-64. 2008 - Publication
Hsieh MC, Das D, Sambandam N, Zhang MQ, Nahl Z. (2008) Regulation of the PDK4 isozyme by the Rb-E2F1 complex. J Biol Chem. 2008 Oct 10;283(41):27410-7. 2008 - Publication
D. Das and M.Q. Zhang. (2007) Predictive Models of Gene Regulation: Application of Regression Methods to Microarray Data. Methods in Molecular Biology, ed. M. Korenberg. 377:95. 2007 - Publication
Hodges E, Xuan Z, Balija V, Kramer M, Molla MN, Smith SW, Middle CM, Rodesch MJ, Albert TJ, Hannon GJ, McCombie WR (2007) Genome-wide in situ exon capture for selective resequencing. Nat Genet. 39:1522-7. 2007 - Publication
Wang X, Bandyopadhya S, Xuan Z, Zhao X, Zhang MQ, Zhang X (2007) PREDICTION OF TRANSCRIPTION START SITES BASED ON FEATURE SELECTION USING AMOSA. Proc. Comp. Sys. Bioinf. Conference. San Diego, Aug. 2007. World Scientific. eProceedings. 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.