Hesham H. Ali, Ph.D
Dhundy (Kiran) Bastola, Ph.D
Dr. Bastola has recently joined the Bioinforamtics faculty in the College of IS&T.
In recent years biological database searching has been solved predominately via local alignment heuristics, pattern matching, and comparison of short statistically significant patterns. While these approaches have unlocked many clues as to sequence relationships, they are limited in that they do not provide searching capabilities based on whole genome or multiple target sequences. The focus of Dr. Bastola's laboratory is in developing alternative approaches to the commonly used heuristic searching method that uses local or global alignment. Relative Complexity Measure (RCM), which calculates organism relatedness based on the overall complexity of the sequences is one such example of alternative approaches. His lab is currently pursuing to implement this approach in the "Advance Molecular Identification System" that has two major components (1) database management system and (2) novel searching algorithm that involves genomic, proteomic, transcriptomic and other high-throughput data.
Zhengxin Chen, Ph.D.
Dr. Chen is a professor in the Department of Computer Science at the College of IS&T. He received his Ph.D. in Computer Science from Louisiana State University. During the fall of 2005, he is teaching CSCI 2980 (Topics: Visualization Bioinformatics), CSCI 8390 (Advanced Topics Database Management), CSCI 9350 (Mathematical and Logical Foundations of Data Mining), and CSCI 4850/8856 (Database Management Systems). He also taught an undergrad/graduate course entitled "Database search and Pattern discovery in Bioinformatics" in the spring of 2005.
His research interests include artificial intelligence, database management systems, intelligent information retrieval, and database search and data mining in bioinformatics. One of his ongoing research topics includes an IST Data Mining project entitled “Text mining for Antimicrobial Peptides.” He is currently supervising a master's thesis for developing an XML Database for RNA data, a master's project for an Electronic Medical Records System with Integrated Clinical Decision Support, and a Ph.D. thesis on text mining. He has also co-chaired a Master’s project on HIV-1 Medicated Neuronal Damage and a thesis on cluster analysis on time series data involving microarrays.
Parvathi Chundi, Ph.D.
Dr. Chundi is an assistant professor in the Department of Computer Science at the College of IS&T. She received her Ph.D in Computer Science from the University at Albany in Albany, NY.
Her research interests include areas like moving object databases, data mining,
bioinformatics, and replicated and distributed databases. Some of her current
research titles include “Text mining of Medline data” and “A
system of moving sensor” related to wireless technology. One current
research topic involves using publicly available domain knowledge to enhance
text mining techniques such as document clustering, text classification, and
trend analysis that are used to extract previously unknown information from
Mark A. Pauley, Ph.D.
Dr. Pauley is a Senior Research Fellow and a professor in the Department of Computer Science in the College of IS&T. He received his Ph.D. in Physical Chemistry from the University of Nebraska-Lincoln. He also did post-baccalaureate studies in Computer Science at the University of North Carolina at Chapel Hill/North Carolina State University. During the fall of 2005, he is teaching CSCI 2980 (Topics: Intro to Web Development) and CSCI 2980 (Topics: Intro to Bioinformatics).
His research interests include object-oriented programming and Bioinformatics. Particularly, the past couple of years, he has worked on making an Affymetrix GeneChip for the rhesus macaque monkey by developing the algorithms and procedures necessary to acquire sequence information from the 3' end of non-human primate orthologs of human genes. He developed software to align mRNA with genomic sequence in order to identify terminal exons of human genes.