Our research focus is on developing methods and software for the analysis of the data from high throughput genomics projects. Particular interests include the analysis of genome sequences and cis-regulatory sequences, using machine learning, evolutional computation and graph algorithms.

Our current research is focused on two main areas: (1). Comparative Genomics: we are interested in detecting a) DNA regulatory motifs; b) Genomic structures such as operons, uberoperons and genomic islands; and c) Biological network and pathways; and (2). Haplotype, SNP and Disease association: we are investigating machine learning approaches to resolve haplotypes, study single nucleotide polymorphisms (SNPs), and their association with diseases.