Machine Learning Approaches to Knowledge Discovery in Genomics Data
Dr. Liangjiang (LJ) Wang
Monday, March 10, 2008
12:00PM ~ 1:00PM, Harris Center 101
Abstract
In this talk, I will describe several machine learning approaches to sequence-based prediction of DNA/RNA binding residues in proteins and genome-wide identification of putative novel transcription factors. I will discuss my current ongoing works on predicting the effect of single amino acid substitutions on protein function and microarray expression data analysis for understanding mental retardation genes. If time permits, I will also talk about my experience with development of biological databases, including the model organism database BeetleBase for functional genomics and the BioStar framework for biomedical data warehouse design.
Short Bio
Dr. Wang received his PhD in Molecular Biology from the University of Georgia in 1999, and his MS in Computer Science from Mississippi State University in 2001. He was a bioinformatics specialist (Research Assistant Professor) at Kansas State University, and now Assistant Professor of Bioinformatics at Clemson University. His research interests include biological databases, machine learning, molecular recognition, gene function and regulation. He has published 17 journal articles and 7 refereed conference papers.
