Computational and Systems Biology
The Computational and Systems Biology specialty 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 and Systems Biology specialty 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
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 UTSW students, staff, and faculty. The backbone of the curriculum consists of a weekly series of alternating student work-in-progress/journal club presentations and seminars by external speakers. 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.
Message from the Chairs
Computational analysis and modeling of experimental data – even if it is not big data – is the backbone of nearly every modern study in the life sciences. Regardless of whether you apply existing methods, create new code, or develop a new mathematical formalism to probe your data, to interpret the outcomes of computational analyses you must understand at least the assumptions and limitations and sometimes also the algorithm underlying the employed methods.
While we are positioning ourselves at UTSW to launch a complete PhD training program in Computational Biology [working title], the existing Computational and Systems Biology specialty curriculum is designed to provide you with an interim forum to learn some key aspects of computational methods in formal didactic courses and informally interact with peers and faculty who push the boundaries in development and/or use of computational approaches in a very broad range of life sciences.
The central events in our curriculum take place every Monday at 11 a.m. in ND11.218, when students of the track present their ongoing research in between seminars by established experts in computational and systems biology. After each presentation/seminar we host a luncheon to promote networking within the rapidly growing community. We look forward to your participation.