Pavel Pevzner, Ph.D. - Margaret O. Dayhoff Lecturer

Ronald R. Taylor Professor of Computer Science & Director, NIH Center for Computational Mass Spectrometry
University of California, San Diego
Biography: 

Pavel Pevzner holds the Ronald R. Taylor Chair in Computer Science, and leads the department's Bioinformatics Laboratory. He joined the UCSD faculty in 2000, following five years in the University of Southern California's Mathematics and Computer Science departments. From 1992-95, he was an associate professor at Pennsylvania State University, where he was affiliated with both the Biotechnology Institute and the Institute for Molecular Evolutionary Genetics. From 1990-92 Pevzner was a postdoctoral researcher at USC. He received his Ph.D in 1988 from the Moscow Institute of Physics and Technology while working (from 1985-90) for what is now Russia's National Center for Biotechnology NIIGENETIKA. Pevzner is the author of the book "Computational Molecular Biology: An Algorithmic Approach" (MIT Press, 2000). He is an executive editor of the "Journal of Computational Biology," and Chair of the Steering Committee of the International Conference on Research in Computational Biology (RECOMB).

Research: 

Computational molecular biology and bioinformatics, including pattern finding, DNA sequencing, DNA arrays, genome rearrangements, computational proteomics.

Professor Pevzner is a leading authority on using computer science to decipher and analyze the human genome. He has written the book (see bio) on computational molecular biology and is currently writing another aimed at undergraduates, "Bioinformatics for Biologists," to present algorithmic ideas in computational biology. Pevzner has developed a new approach to discovery of subtle regulatory patterns in DNA sequences (motif finding). His laboratory has produced a new EULER algorithm and web server to assemble DNA fragments as well as the GRIMM algorithm and web server for genome rearrangement analysis. Pevzner actively collaborates with biologists on studying rearrangements in human, mouse, cat, and cow genome sequences, and on prediction of regulatory motifs.

Title of Presentation: 
Antibiotics Discovery: From Genome Sequencing to Genome Mining to Spectral Networks
Abstract : 

Genomics studies revealed numerous antibiotics-encoding genes across a wide range of bacterial and fungal species, including various species in the human microbiome. However, little is known about the hundreds of secondary metabolites (including antibiotics!) produced by microorganisms in the gut, despite the fact that humans are chronically exposed to them. Deep exploration of this meta-antibiome critically depends on a transition from the current one-off process of antibiotics analysis to a high-throughput antibiotics sequencing. I will discuss recent advances in computational antibiotics discovery that span bioinformatics techniques ranging from genome sequencing to genome mining to spectral networks.