Research Interests:

Proteomics and Bioinformatics

For a list of Dr. Nesvizhskii's most recent publications, click here.

Brief Biography:

Dr. Nesvizhskii received an M.S. (with honors) from St. Petersburg State Technical University, Department of Physics and Technology, St. Petersburg, Russia in 1995 and a Ph.D. in Physics from the University of Washington, Seattle in 2001. He completed postdoctoral training in Ruedi Aebersold Lab at the Institute for Systems Biology in Seattle, Washington from 2001-2003 and joined the staff as a Research Scientist upon completion of training.

Dr. Nesvizhskii was the recipient of a medal for "Best Student Scientific Work" awarded by the Russion Federation State Committee of Higher Education and was named Russian Presidential Fellow for the period 1994-1995 and Soros Fellow for the period 1995-1996. He is a member of the Human Proteome Organization (HUPO), International Society for Computational Biology, and the American Society for Mass Spectrometry.

In November 2005, Dr. Nesvizhskii joined the faculty of the Department of Pathology as an Assistant Professor.

Dr. Nesvizhskii’s research interest is in the field of quantitative proteomics, with a focus on the development of computational methods for processing and extracting biological information from complex proteomic datasets. Similar to other global high throughput technologies such as microarray gene expression analysis, proteomics is extremely dependent on the ability to quickly and reliably analyze large amounts of experimental data. One of the aims of Dr. Nesvizhskii’s research is to close the critical gap between the development of high throughput quantitative proteomics methods and the ability to deal with the resulting data deluge and to convert it into new biological knowledge or to develop new disease biomarkers. The efforts in his lab range from the development of computational tools and statistical methods for mass spectrometry-based peptide and protein identification and quantification, to the establishment of guidelines and standards for proteomic data analysis and publication, to the creation of public databases and proteomic data repositories and integration of proteomic with genomic and other types of biological data.