Phylogenies are of fundamental interest to evolutionary biologists and form the basis for much biological research. Within phylogenetics, computational challenges abound because almost all the major problems are technically NP-hard and also hard in practice.

A history of interaction between computational and biological scientists in phylogenetics—many at The University of Texas—has led to significant changes in the ways biologists design and select tools to analyze their data. Nonetheless, considerable potential still exists for significant advances in research methodologies and data analysis tools, as well as for the development of new applications in phylogenetics through the incorporation of mathematical and computational approaches.

With the successful completion of various genome sequencing projects, the collection of very large comparative datasets, and new methods for acquiring morphological data, the need for advances in computational and applied phylogenetics is extremely pressing. There is a need to develop methods for using large datasets, methods for new character types, and methods for comparing, interpreting, and visualizing large trees. This development is critical to solving problems such as the inference of deep or reticulating branches in the Tree of Life, and the phylogenetic information is critical to interpreting all biological systems.

 

The Integrative Graduate Education and Research Traineeship (IGERT) program at The University of Texas brings together biologists and computer scientists—faculty and graduate students—in a program designed to foster interactions and collaborations between the two groups.These interactions are leading to development of new phylogenetic methods and models as well as applications of those innovations throughout biology.

To train graduate students who can bridge biology and computer science, we devote considerable attention to breaking down the barriers between these disciplines. We create a physical and cultural learning environment that facilitates interactions among computational scientists and biologists.

Currently, computational scientists and biologists often take very different approaches to phylogenetics, and most graduate programs do not integrate computational and applied aspects of phylogenetics. This program trains graduate students who understand and contribute to both sides the discipline.

 

The IGERT program at The University of Texas has four major goals:

• Design and implement an interdisciplinary training curriculum in the computational and biological sciences that prepares graduate students to understand and contribute to both sides of computational biology.

• Stimulate interdisciplinary graduate research and interdisciplinary interactions in general between computational scientists and biological scientists that will lead to development and testing of novel approaches to unsolved problems in phylogenetics and their application to problems in biology.

• Prepare trainees for their careers beyond graduate school and help them achieve visibility in the larger research community.

• Evaluate and improve the program in computational and applied phylogenetics to ensure its success beyond the IGERT project.