Faculty

The Faculty in the UNTHSC College of Biomedical and Translational Sciences (SBS) have broad research interests across the biological and medical disciplines. The core faculty in Genetics teach in several of the CBTS core curriculum and program–specific courses. Generally, faculty serving as mentors or on student committees are active in the Genetics discipline or other disciplines within the Department of Microbiology, Immunology and Genetics. Students in Genetics may choose to include faculty from any of the other Departments, Disciplines or Colleges on their advisory committees. Our core faculty are listed below. Also see the list of Affiliated Faculty (add intra-page hyperlink) below for faculty names and research interests from other disciplines and Schools. Many of these faculty, although their specialization is focused on particular areas in biomedical science, often address questions that have an inherent genetic component enabling students and mentors to craft highly valuable, interdisciplinary projects. Prospective students are highly encouraged to make contact with the Graduate  Advisor  and our faculty to discuss mutual areas of research interest.

Michael S. Allen, Ph.D. Associate Professor  Tick Testing Laboratory
Research in the Allen Laboratory focuses on microbiology of vector-borne diseases and microbiome-host studies of human and animal systems.  The former includes testing of all ticks submitted to the state of Texas for the presence of specific bacterial pathogens, and research into the factors influencing disease transmission and pathology.  Microbiome research includes investigation of complex bacterial communities and their interactions with a wide variety of hosts (humans, arthropod vectors of disease, etc.), defining factors that disrupt or support microbial community assembly and structure, exploring community dynamics in polymicrobial diseases of different organ systems (e.g. gut, lung), development of genetically engineered probiotics for the treatment of disease, and applications of microbiome research to problems in forensic science.

Robert Barber, Ph.D. Associate Professor, Department of Pharmacology and Neuroscience
Dr. Barber’s research interests include investigations of how DNA methylation and microRNA expression impact risk for neurodegeneration; efforts to use patterns of DNA variation to predict the age at onset of Alzheimer’s disease (AD); and scanning the intestinal microbiome to determine how an individual’s profile of gut bacteria may impact their cognitive ability as they age. He is also interested in AD pathophysiology among Mexican Americans and how disease mechanisms differ between members of this underrepresented ethnic group and Caucasians. Students in my lab are trained in the analysis of large genetic and biomarker data sets through collaborations with several researchers at UNTHSC and other Texas Alzheimer’s Research & Care Consortium institutions, as well as the University of North Carolina at Chapel Hill.

Michael D. Coble, Ph.D., Associate Professor, Director UNT Center for Human Identification
DNA evidence from crime scenes (including evidence from victims of sexual assault) can often contain mixtures of two or more contributors and can be challenging for the forensic scientist to interpret. Our research focuses on issues associated with DNA mixture interpretation and probabilistic methods of interpretation using software analyses. Other areas of research include haploid marker systems for forensic testing (mitochondrial DNA and Y-chromosome testing), and non-traditional marker systems (e.g. X-chromosomal STRs, insertion-deletion markers, etc.) to increase genetic information from challenged samples.

Nicole Phillips Assistant Professor
Dr. Phillips’ research interests lie in the study of genetic interactions that contribute to one’s risk for developing complex, age-related diseases. The bulk of her wet lab work has focused on the role of mitochondrial genetics in the progression of late onset Alzheimer’s disease. She has investigated several indices of mitochondrial DNA integrity as related to disease progression using the longitudinal samples from the Texas Alzheimer’s Research and Care Consortium (TARCC). Dr. Phillips served as one of the primary analysts in a genome wide association (GWA) analysis of the same TARCC Alzheimer’s disease cohort.  This work aimed to identify genomic regions that are associated with the blood-based biomarkers associated with Alzheimer’s disease and regions associated with the mitochondrial DNA integrity indices established in her laboratory. Dr. Phillips continues to build on her prior work with TARCC, using both in silico and experimental approaches. While she has found her passion in the study of Alzheimer’s disease, she also looks forward to extending her research to other age-related, complex diseases.

August Woerner, Ph.D. Research Assistant Professor
Dr. Woerner is a Research Assistant Professor in Dr. Budowle’s research group. He has a M.S. in Computer Science and Ph.D. in Genetics from the University of Arizona. His research interests are generally in the areas of computation and population genetics, with a focus in forensics, bioinformatics and machine learning. His current research projects run the gamut from streamlining bioinformatics pipelines, making them faster and more user friendly, to machine learning and statistical approaches to processing and calling MPS data, to inference problems in population genetics and genomics.

Yan Zhang, Ph.D. Research Assistant Professor
Dr. Zhang has interests in how the microbiome and host interact in health and disease. Her projects include tick microbiome and disease associated human microbiome, using genomic and metagenomic approaches to investigate the microbiome dynamics and understand its role in disease development (such as tick born disease, Phenylketonuria, Alzheimer’s disease, inflammation after severe injury and etc). Dr. Zhang provides services for Next Generation Sequencing using IonTorrent and Miseq platform. She also develops bioinformatics and statistical tools for metagenomic analysis.