research guide - UTEP Magazine - University of Texas at El Paso

Mining genetic information
for answers to disease
In the field of biology, the beginning of the 21st
century will be remembered for a “Big Bang” of genetic
information—the completion of the first survey of the
entire human genome.
The genetic blueprint of human beings, the human
genome presents researchers with billions of bits of genetic
information waiting to be mined for ways to prevent,
diagnose and cure diseases.
This ever-expanding amount of human and
other genetic information has given rise to the field
of bioinformatics, which brings together the power of
mathematics, statistics and high-performance computing
to tackle complex biological problems.
At UTEP, faculty and master’s-level students in the
Bioinformatics Program are conducting a wide range of
research, from investigating gene therapies for diseases to
developing powerful software tools for genetic scientists.
For the computationally intensive applications
required by their research, the bioinformatics teams tap
into the power of UTEP’s high-performance computing
resources, including IBM eServer p590 and p690 machines
and a Cray XD1 Linux Cluster.
The Bioinformatics Program is directed by Ming-
Ying Leung, Ph.D., professor of mathematical sciences,
whose own research focuses on using probabilistic
modeling and scan statistics to study genetic sequences.
Her work has shed light on the workings of the virus
that causes Severe Acute Respiratory Syndrome and the
replication behavior of herpesvirus genomes.
Leung also is focusing on projects that will improve
the mathematical and computational tools available to
bioinformatics researchers. With the support of a four-year,
$594,000 award from the National Institutes of Health,
she is developing a set of open-source
grid-computing software tools to predict
genome structures in RNA viruses.
Also, the National Science Foundation
is funding Leung’s four-year, $416,000
project to develop mathematical models
for the prediction of RNA secondary
structures in large RNA molecules.
Research Assets
Bioinformatics Program –
www.bioinformatics.utep.edu
• DNA sequence assembly and analysis
• Ecology and phylogeny
• Microarray and proteomics data analysis
• RNA and protein structure prediction
Ming-Ying Leung, Ph.D.
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