The general focus of Dr. Valafar’s current research is the application and transfer of engineering techniques to biological systems. In addition, this transfer of information can be reversed to implement efficient optimization and security (immunity) techniques inspired by biological models. His specific research is divided into two main categories: Computational Biology and Computational Medicine.
Our specific interest in the area of Computational Biology is the problem of protein folding. Current approaches to protein folding are segregated into either experimental or computational means of structure determination. Our approach to protein folding can be viewed as a hybrid of the above two main approaches. While traditional methods of structure determination remain to be the most reliable approaches to characterization of structure and dynamics of biomolecules, they have imposed certain tangible limitations on the whole process of rapid and accurate structure determination. On the other hand, the recently emerging approaches to computational structure determination offer a very cost effective means of structure determination while suffering from unconfirmed results.
Our hybrid approach utilizes only 2% of the experimental data required for traditional methods of structure determination while reducing the computational requirement of protein folding problem to a polynomial time complexity. This is possible through a careful consideration of the source of experimental data. In our studies, we choose Residual Dipolar Couplings (RDC) as the main source of experimental data.
Current investigation of the molecular basis for a number of diseases have been unsuccessful. This lack of success has steered the future investigation in the study of disparate data in order to understand the relationship between the environment and the genome. In our view a very important aspect of this interaction is neglected. That is the temporal component of the interaction. Examples borrowed from controls in the design of stable systems stress the importance of temporal component in the modeling of any electrical circuit. The same argument and therefore engineering techniques should be transferable to the study of stable biological systems. Our long term goals of study is therefore a temporal effects of external stimulants on the behavior of cells with given genome. Our short term goal is to develop a physiological state response of individual patients. Our studies include response of Sickle Cell Anemia patients to Hydroxyurea and study of differential expression profiling in patients suffering from cervical cancer.
1200 Catawba Street, Room 301
Department of Computer Science and Engineering
University of South Carolina
Columbia, SC 29208