ITR/AP(BIO): Algorithmic Study in Computational Proteomics

University Of Southern California, Los Angeles CA

Investigators

Abstract

EIA-0112934 Ting Chen University of Southern California Title: ITR/AP(BIO): Algorithmic Study in Computational Proteomics The main focus of this project is on developing computer algorithms and programs to support a technology called High Performance Liquid Chromatography (HPLC)-Tandem Mass Spectrometry (MS-MS), a very powerful tool for high-throughput protein identification. This technology generates mass patterns for peptides, and relies on fast and accurate computer algorithms to map mass patterns to peptide sequences. This project aims at designing algorithms for multiple proteomic applications. This project addresses four fundamental computational problem areas in Proteomics: (1) the problem of peptide identification (2) the problem of de novo peptide sequencing, which aims to sequence peptides directly from tandem mass spectra without database search, (3) the problem of identifying protein cross-linking sites, which looks for a pair of cross-linked peptide sequences optimally correlated to a tandem mass spectrum, and (4) the problem of peptide mass fingerprinting, which aims to identify proteins by their masses of enzyme-digested peptide mass patterns. Novel and efficient algorithms are being designed to solve these problems.