The core theme of my research career is the development of methods of next-generation sequence analysis to address key issues in HIV treatment and prevention. I draw on a highly multidisciplinary background that covers mathematical biology1, experimental virology2, and bioinformatics3. More recently, I have been developing bioinformatic techniques to detect compensatory interactions from the comparative analysis of genetic sequence data.
Research Sumary:

I am actively developing computational tools to analyze next-generation sequencing (NGS) data. NGS is a major challenge for bioinformatics because of the overwhelming amounts of sequence data generated by these technologies. For example, a single Roche/454 Genome Sequencer FLX run typi- cally generates approximately 100,000,000 bps of data. The vast majority of HIV studies have limited themselves to straight-forward analyses such as quantifying the number of rare sequence variants in an HIV-1 population. My objective is to test the limits of what can be inferred from these data. Additionally, I have been developing techniques to reconstruct the complete history of HIV evolution within hosts from longitudinal NGS data. For example, I have used these techniques to reconstruct the mutational pathways leading to the first CXCR4-using ancestors, thereby recreating the evolutionary dynamics of the ‘HIV coreceptor switch’.