The Computational Biology Track curriculum is designed to help students learn how to leverage mathematical and computational approaches to understand biological and chemical processes. For more details, review the Computational Biology Degree Plan.
Any student pursuing a Ph.D. with a background and interest in this field can add a Computational Biology Track to his or her Ph.D.
Mathematical and computational concepts, methods, and algorithms are being applied to all areas of basic and clinical life sciences, which results in a variety of research topics. Examples include:
- Biophysics and Structural Biology – Protein structure and function prediction; analysis of biological sequences and 3D structures; macromolecular interactions and biological networks; molecular evolution
- Chemical Biology – Analysis of small organic molecules; design of materials and drugs; chemical dynamics
- Genetics and Genomics – Analysis of DNA/RNA sequences; genome association to cellular and organismal function; statistical genetics
- Imaging – Computer vision and pattern recognition applied to medical imaging and microscopy data, statistical and mathematical modeling of the spatiotemporal organization of image events from molecular to macroscopic scales.
- Medical Informatics – Machine learning of patterns in multivariate clinical databases, predictive modeling of clinical outcomes by variable association
- Systems Biology – Computational reconstruction and analysis of biological networks; modeling of complex, nonlinear systems; spatiotemporal integration of chemical and mechanical processes across scales
Going Beyond Lab Research
- Advanced Coursework
The curriculum offers a selection of elective courses that introduce some of the computational, mathematical, and statistical foundations of these applications. The curriculum course series is complemented by a growing offering of nanocourses that are open to all UT Southwestern students, staff, and faculty.
- Works-in-Progress Seminars, Journal Clubs, Speaker Series
The backbone of the curriculum consists of a weekly series of alternating student works-in-progress/journal club presentations and seminars by external speakers.
- Fellows Program
Students can also apply for participation in the fellows programs in the Bioinformatics Core Facility and in the Bio High Performance Computing facility. These unique programs offer co-mentorship for portions of the dissertation research to graduate students affiliated with a life science or clinical lab in the areas of computational biology and information technology.