Bioinformatics and Computational Biology

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Track Representative Robin Gutell

The Bioinformatics and Computational Biology Track is comprised of a highly interdisciplinary and collaborative group of researchers who are interested in biological problems that frequently involve the collection and analysis of large datasets, and who undertake engineering and applied approaches to these problems. Some of the members of this track work closely with the Center for Systems and Synthetic Biology (cssb.utexas.edu) on mapping and analyzing interaction networks and signal transduction pathways. The members of this track are also frequent participants in a number of training or joint grants, including IGERT grants on Optical Molecular Biology or Computational Phylogenetics, an ARO-MURI on biosensor development, and a Beckman Foundation grant for microarray technologies.

Our commitment to interdisciplinary research is not only manifest within the Track, but extends beyond the Track as well. Interactions and collaborations with investigators from other Tracks are highly encouraged. Students who do well in this Track frequently demonstrate individual initiative in generating and executing projects. In order to craft interdisciplinary projects, students are encouraged to have more than one mentor during their graduate careers.

In addition to the global requirements of the Cell and Molecular Biology program that ensure that trainees have a strong grounding in the biological sciences, students must meet the following Track requirements:

  1. Demonstrate competence in computer programming. It is expected that all Track students can program in at least one language. A particular language is not specified since the language of choice varies across different research applications. This competency can be demonstrated through coursework or through practical experience.

  2. Demonstrate competence in the fundamentals of biostatistics. It is expected that all Track students can interpret and perform basic statistical analyses and can communicate effectively with a statistician for more sophisticated analyses. This competency can be demonstrated through coursework or through practical experience.

  3. Take at least one course at the interface of computational methods and biological sciences. This experience is intended to supplement and help prepare the student for the more intensive interdisciplinary training of the dissertation research. The following courses are examples of those that can be taken. Other courses can fulfill this requirement with consent of the Track representative.

    1. BIO 384K Recent Advances in Computational Biology

    2. BIO 384K Computational Phylogenetics and Applications to Biology (I & II)

    3. BME 341 Computational Genomics Lab

    4. BME 383J Computational Structural Biology

    5. BME 385J Genomic Signal Processing and Bioinformatics

    6. CH 391L Bioinformatics

    7. CS 395T Algorithms for Computational Biology

  4. Participate in the Track journal club. At journal club meetings, students take turns leading discussion on recent articles and more senior students give presentations on their own research.

Bioinformatics and Computational Biology Tracks and Research Focus Areas
 
Aldrich, RichardAnslyn, Eric V.Appling, Dean
Atkinson, NigelBajaj, ChandrajitBarrick, Jeffrey
Brown, Richard M.Bull, James J.Chen, Z. Jeffrey
Contreras, LydiaDalby, KevinElber, Ron
Ellington, AndyGeorgiou, GeorgeGutell, Robin
Harris, AdronHassibi, Arjang Hillis, David
Hofmann, Hans A.Iverson, BrentIyer, Vishwanath
Jansen, RobertJohnson, KennethKerwin, Sean
Kim, JonghwanKitto, G. BarrieKrug, Robert
Lambowitz, Alan M.Liu, Hung-wen (Ben)Makarov, Dmitrii
Marcotte, EdwardMarkey, MiaMartin, Stephen
Meyers, Lauren AncelMiranker, DanielMolineux, Ian
Payne, ShelleyPoenie, MartinPress, William
Ren, PengyuRobertus, JonSchmidt, Christine
Stevens, ScottWarnow, TandyWilke, Claus
Xhemalce, Blerta

CMB Graduate Program