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About our Work

• Systematic biologists have long worked toward discovering the evolutionary relationships which connect all living
  species, however advances in sequencing techniques over the past several decades have resulted in an
  abundance of data that cannot be analyzed manually.


• Our research group designs computational methods for phylogenetic inference and the related problem of
  multiple sequence alignment. In particular, we attempt to infer structures called phylogenies which represent
  evolutionary relationships among biological data; multiple sequence alignment methods attempt to find
  homologous sites among sets of varying-length strings which represent nucleic or amino acid sequences. We
  use the methods we design to help scientists from around the world analyze their data.


• The formalized phylogeny reconstruction and sequence alignment problems are computationally difficult, as all
  good approaches attempt to solve NP-hard optimization problems. As such, state-of-the-art methods in
  computational phylogenetics draw on methods from a wide array of fields: mathematics, algorithm design,
  theoretical computer science, experimental algorithmics, parallel programming, statistics, artificial intelligence,
  and machine learning. Moreover, the field offers opportunities for work in other areas such as data
  visualization and historical linguistics. Modern research in phylogenetics is an active and highly-interdisciplinary
  endeavor.

How to Join

• If you'd like to learn more about our work, you'll want to check out our resources page for relevant tutorials,
  presentations, and courses here at UT. You can learn about what projects we're working on, read some of
  our publications, and sit in on our weekly journal club. If you are interested in joining our lab, please read
  this note and feel free to contact one of us.


• Our lab is part of the Center for Computational Biology and Bioinformatics (CCBB), which provides research
  support and opportunities for students, postdoctoral fellows, and faculty interested in the use of computational
  approaches to solving biological problems. We are also affiliated with several other research centers on campus.
  There are no specific degree programs in computational biology, but computational biology tracks are available
  in several degree programs; doctoral students have the opportunity to work with participating faculty from
  departments throughout UT.