Document Type

Journal Article

Department/Unit

Department of Computer Science

Language

English

Abstract

Background: Tandem mass spectrometry-based database searching is currently the main method for protein identification in shotgun proteomics. The explosive growth of protein and peptide databases, which is a result of genome translations, enzymatic digestions, and post-translational modifications (PTMs), is making computational efficiency in database searching a serious challenge. Profile analysis shows that most search engines spend 50%-90% of their total time on the scoring module, and that the spectrum dot product (SDP) based scoring module is the most widely used. As a general purpose and high performance parallel hardware, graphics processing units (GPUs) are promising platforms for speeding up database searches in the protein identification process.Results: We designed and implemented a parallel SDP-based scoring module on GPUs that exploits the efficient use of GPU registers, constant memory and shared memory. Compared with the CPU-based version, we achieved a 30 to 60 times speedup using a single GPU. We also implemented our algorithm on a GPU cluster and achieved an approximately favorable speedup.Conclusions: Our GPU-based SDP algorithm can significantly improve the speed of the scoring module in mass spectrometry-based protein identification. The algorithm can be easily implemented in many database search engines such as X!Tandem, SEQUEST, and pFind. A software tool implementing this algorithm is available at http://www.comp.hkbu.edu.hk/~youli/ProteinByGPU.html. © 2014 Li et al.; licensee BioMed Central Ltd.

Publication Date

4-2014

Source Publication Title

BMC Bioinformatics

Volume

15

Issue

121

Start Page

1

End Page

11

Publisher

BioMed Central

Peer Reviewed

1

Copyright

© 2014 Li et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution 2.0 Generic License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

Funder

This work was supported by research grants FRG2/10-11/099 and FRG2/ 11-12/158 from Hong Kong Baptist University.

DOI

10.1186/1471-2105-15-121

Link to Publisher's Edition

http://dx.doi.org/10.1186/1471-2105-15-121

ISSN (print)

14712105

ISSN (electronic)

14712105

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