A Scalable Parallel Approach for Peptide Identification from Large-Scale Mass Spectrometry Data

Identifying peptides, which are short polymeric chains of amino acid residues in a protein sequence, is of fundamental importance in systems biology research. The most popular approach to identify peptides is through database search. In this approach, an experimental spectrum ("query") generated from fragments of a target peptide using mass spectrometry is computationally compared with a database of already known protein sequences. The goal is to detect database peptides that are most likely to have generated the target peptide. The exponential growth rates and overwhelming sizes of biomolecular databases make this an ideal application to benefit from parallel computing. However, the present generation of software tools is not expected to scale to the magnitudes and complexities of data that will be generated in the next few years. This is because they are all either serial algorithms or parallel strategies that have been designed over inherently serial methods, thereby requi...

• Type: Journal
• Year: 2009
• Where: ICPPW
• Authors: Gaurav Ramesh Kulkarni, Ananth Kalyanaraman, William R. Cannon, Douglas J. Baxter
• Keywords: Database, Distributed And Parallel Computing, ICPPW 2009, Peptide, Target Peptide