The effort to build a faculty group in computational biology and ioinformatics began in 1999. The department was motivated by the desire to create a critical-mass of faculty in this important emerging research area, to diversify its research portfolio through the addition of access to NIH funding, and to become a leading force in the deep and continuing interaction between computer science and the life sciences during the proclaimed "Century of Biology." The department's bioinformatics initiative was launched through a joint proposal by the department and the Virginia Bioinformatics Institute (VBI) to the state's Commonwealth Technology Research Fund. This proposal positioned the department to hire five faculty in bioinformatics. The bioinformatics group has now grown to include 12 core faculty (including four VBI faculty with joint appointments in Computer Science), as well as seven affiliated faculty.

Computational and Evolutionary Genomics

URL: http://bioinformatics.cs.vt.edu/~zhanglab
Contact: Liqing Zhang

We analyze genomes to infer interesting evolutionary events, with a focus on the divergence of duplicated genes in both primary sequences and function. We develop methods to analyze the human SNPs (single nucleotide polymorphisms) to understand the associations between different genetic diseases. We also develop open source software and online databases for analyzing high throughput data. We are currently developing a program for detecting gene conversion (non-reciprocal transfer of genetic information from one sequence to another) using machine learning approach.

Computational Biology Lab

URL: http://people.cs.vt.edu/~ycao
Contact: Yang Cao

Our group focuses on the development of multiscale, multiphysics modeling and simulation methods and tools that help biologists build, simulate and analyze complex biological systems, simulate their dynamics and analyze their functions. Typical biological models include gene expression models, protein interaction networks, and cell cycle models. We are paricularly interested in applications where multiple scales and multiple physics are presented, and has to be modeled in a hybrid way that include both discrete and continuous variables, deterministic and stochastic equations.

We work at the interface of mathematics, computer science, biology and other related subjects. Due to the interdisciplinary feature, we collaborate with other groups with different background.

Computational Systems Biology Research Group

URL: http://bioinformatics.cs.vt.edu/~murali/research.html
Contact: T. M. Murali

The functioning of a living cell is governed by intricate networks of physical, functional, and regulatory interactions among different types of molecules. The goal of our research is to build phenomenological and predictive models of these networks by developing approaches based on graph theory, data mining, and machine learning. We drive this work through collaborations with computer scientists and with life science researchers spanning diverse fields including biochemistry, infectious diseases, plant pathology, and tissue engineering.

Laboratory for Advanced Scientific Computing and Applications

URL: http://research.cs.vt.edu/~lasca/
Contact: Layne Watson

The goal of the Laboratory for Advanced Scientific Computing and Applications (LASCA) is to provide expertise and leadership in high-end scientific computing research and education at Virginia Tech. Located in Torgersen Hall, the laboratory is a visible and strategic center of activity in applied high-computation and assist scientists and engineers in applying high-end computing resources to their problems. By bringing together experts in scientific cp\omputing and its applications, LASCA helps build the kind of multidisciplinary teams needed to address today's most challenging computational science problems.

Sequence Analysis and Gene Silencing

URL: https://bioinformatics.cs.vt.edu/cmgs/CMGSDB/
Contact: Lenwood Heath

This laboratory houses the Computational Modeling of Gene Silencing (CMGS) project. This project is constructing computational models of the gene silencing phenomenon for the microscopic worm Caenorhabditis elegans. One product of the project is a comprehensive database of information about gene silencing in C. elegans, CMGSDB. Data mining techniques play a large role in the computational modeling. This laboratory also features research in biological sequence analysis. One topic in that area is genomic signatures, mathematical structures that can be computed from genomic sequences and used to identify the original organism.

Structural Bioinformatics and Computational Molecular Biophysics

Contact: Alexey Onufriev

Our group uses computational methods to understand dynamics and function of large biomolecular systems such as proteins, DNA, and their complexes. Some of these methods are being developed in our lab. The computations are often performed on supercomputers such as VT's System-X.