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Computational Biology

The Computational Biology Track curriculum is designed to help students learn how to leverage mathematical and computational approaches to understand biological and chemical processes.

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.

Research Topics

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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

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  • 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.

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