Bogdan, I.A., Coca, D. and Beynon, R.J. (2009) Peptide mass fingerprinting using field-programmable gate arrays. IEEE Transactions on Biomedical Circuits and Systems , 3 (3). pp. 142-149. ISSN 1932-4545
Abstract
The reconfigurable computing paradigm, which exploits the flexibility and versatility of field-programmable gate arrays (FPGAs), has emerged as a powerful solution for speeding up time-critical algorithms. This paper describes a reconfigurable computing solution for processing raw mass spectrometric data generated by MALDI-TOF instruments. The hardware-implemented algorithms for denoising, baseline correction, peak identification, and deisotoping, running on a Xilinx Virtex-2 FPGA at 180 MHz, generate a mass fingerprint that is over 100 times faster than an equivalent algorithm written in C, running on a Dual 3-GHz Xeon server. The results obtained using the FPGA implementation are virtually identical to those generated by a commercial software package MassLynx.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Keywords: | Biomedical computing; field-programmable gate arrays (FPGAs); mass spectrometry; optimization methods; proteins |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Miss Anthea Tucker |
Date Deposited: | 08 Mar 2010 09:39 |
Last Modified: | 09 Jun 2014 18:36 |
Published Version: | http://dx.doi.org/10.1109/TBCAS.2008.2010945 |
Status: | Published |
Publisher: | IEEE-INST |
Identification Number: | 10.1109/TBCAS.2008.2010945 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:10484 |