- Last Updated on Friday, 20 September 2013 16:18
This is the third in a series of profiles on users of UTEP’s high performance computing capabilities. To learn more, click here.
By Nadia M. Whitehead
UTEP News Service
Ribonucleic acid (RNA) is a complex molecule found in all life forms, and it plays an important role in protein synthesis and other cellular chemical activities.
“You can think of RNA as a long chain of beads strung together,” said Ming-Ying Leung, Ph.D., professor in the mathematical sciences department and director of bioinformatics at The University of Texas at El Paso. “There are hundreds to thousands of beads chained together – each one of four colors representing the nucleotide bases adenine, guanine, cytosine and uracil.”
To complicate the structure further, the chain can fold up into various shapes that determine its biological functions. In studying RNA activities, scientists need to know exactly what these structures look like.
Leung is out to unveil these structural shapes, in particular those of nodaviruses – a family of viruses that cause diseases in fish and insects. One of the diseases is known as Viral Nervous Necrosis, which can lead to mortality rates as high as 100 percent.
“This virus has the ability to affect our agricultural system,” the mathematician said. “We need to find a way to stop the virus from replicating, and its RNA structure has a lot of bearing on this ability.”
By using UTEP’s high performance computing system, Leung is able to create mathematical models and use the system to predict the RNA structures of nodaviruses. The goal is to help virologists figure out a way to alter the RNA structures of these viruses and control their replication process.
“There would be no way for us to solve this problem if there wasn’t high performance computing here at UTEP,” she said. “Bioinformatics is an area where you tackle those biological problems with a lot of data. We need to have powerful machines to process all the information.”
She added, “If we can find a good computing algorithm to find out the virus’ RNA structure, we could potentially use the same thing to look into the genetic RNA of other viruses that are even more dangerous, such as the flu viruses and HIV that have caused multiple epidemics worldwide.”