Modern biology is unimaginable without sequence analysis, and sequence analysis is impossible without bioinformatics tools and statistical methods. Over the past twenty years, our group have been developing both, and applying them, almost always with a large number of interdisciplinary collaborators, to the study of various systems, especially viral pathogens (HIV-1, Influenza A virus, Ebola virus, etc.).
Our research is not limited to any particular system, any particular set of evolutionary questions, or any particular methodological or computational approach: rather we try to identify and implement a practically useful, and statistically justifiable solution to a particular problem. We focus on delivering high quality, computationally efficient and user friendly scientific software offering solutions to questions like this:
- How does one extract evolutionary imprints left by the action of natural selection, recombination, and other processes on sequence data (www.datamonkey.org)?
- How can sequence data be used to understand the dynamics of pathogen transmission (especially HIV-1, www.hiv-trace.org)?
- How does one mine deep sequencing data to understand within-host evolution of pathogens and the concommitant immune response (www.antibodyo.me)?
- How can one deliver software that allows to test various evolutionary hypotheses (www.hyphy.org)?