Andrei Osterman is an Associate Professor in the Bioinformatics and Systems Biology Program at the Infectious and Inflammatory Disease Center of Sanford-Burnham Medical Research Institute (since August 2003). He received his doctorate from Moscow State University in 1983, did postdoctoral work UT Southwestern Medical Center, and held the position of the Director and then Vice President of Research at Integrated Genomics in 1999-2003. Dr. Osterman is one of the founders of the Fellowship for Interpretation of Genomes (FIG), a nonprofit research organization that launched the Project to Annotate 1,000 Genomes in 2003. FIG provides the open-source integration of all publicly available genomes and tools for their comparative analysis, annotation, and metabolic reconstruction.

The main focus of Dr. Osterman’s research team is on fundamental and applied aspects of the key metabolic subsystems in a variety of species, from bacteria to human. This group uses a systems biology approach to reconstruct and explore metabolic and transcriptional regulatory networks. This approach combines comparative genomics and other bioinformatic techniques with biochemical and genetic experiments for pathway, gene and target discovery. Using this approach this group predicted and experimentally verified numerous enzyme families in the metabolism of cofactors, carbohydrates, and amino acids. Recent breakthroughs included prediction and characterization of novel transporters, transcriptional regulators and carbohydrate utilization pathways in a number of model bacterial systems. Applications in the field of infectious disease include identification of novel drug targets and structure-based development of novel anti-infective agents. New directions in cancer research are based on application of metabolic profiling technology for identification of novel diagnostic and therapeutic targets. Other directions of the on-going research include bioinformatics of regulatory proteolysis and applications of structural modeling for exploration of metabolic networks and gene discovery.