Our laboratory was officially established in 2006 with the goal of uniting ongoing bioinformatics research in the department. We focus on developing and applying computational techniques for the analysis of data and modeling of processes related to molecular biology. The broad aim of our research is to provide computational tools to assist researchers in understanding, explaining, and predicting the behavior of complex biological systems. We utilize methodologies from the areas of machine learning, statistical modeling, graph theory to provide solutions to bioinformatics problems such as protein functional classification, gene expression analysis, protein-protein interaction network analysis. To give a couple of examples, we work on machine learning techniques for feature extraction and feature selection for protein sequences, we work on extraction of gene expression patterns and try to explore a group of genes with similar behaviors for gene expression arrays, and we integrate multiple data sources using statistical techniques to construct and analyze these networks for protein-protein interaction networks.