We focus on developing innovative and efficient methods to analyze large DNA sequence data sets in order to provide genome-scale understanding of cellular function. Our current and past research contributions integrate sophisticated machine learning techniques and statistical methods that answer questions such as:

• What are the exon-intron structures of genes?
• How do we use RNA sequencing to restructure the splice variants that are transcribed in different cell types and conditions?
• How do we use sequence data to determine the levels of gene expression?