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Bioinformatics Advance Access originally published online on August 5, 2004
Bioinformatics 2004 20(18):3628-3635; doi:10.1093/bioinformatics/bth460
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Bioinformatics vol. 20 issue 18 © Oxford University Press 2004; all rights reserved.

Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting

Jim Samuelsson 1, Daniel Dalevi 2, Fredrik Levander 3 and Thorsteinn Rögnvaldsson 4,*

1 Genedata GmbH, Lena-Christ-Strasse 50, 82152 Martinsried, Germany, 2 Computing Science, Chalmers University of Technology, SE-412 96 Göteborg, Sweden, 3 Department of Protein Technology, Lund University, Sölvegatan 33A, SE-223 62 Lund, Sweden and 4 School of Information Science, Computer and Electronic Engineering, Halmstad University, Box 823, SE-301 18 Halmstad, Sweden

Received on February 20, 2004; revised on May 13, 2004; accepted on July 27, 2004
Advance Access Publication August 5, 2004

Summary: A set of new algorithms and software tools for automatic protein identification using peptide mass fingerprinting is presented. The software is automatic, fast and modular to suit different laboratory needs, and it can be operated either via a Java user interface or called from within scripts. The software modules do peak extraction, peak filtering and protein database matching, and communicate via XML. Individual modules can therefore easily be replaced with other software if desired, and all intermediate results are available to the user. The algorithms are designed to operate without human intervention and contain several novel approaches. The performance and capabilities of the software is illustrated on spectra from different mass spectrometer manufacturers, and the factors influencing successful identification are discussed and quantified.

Motivation: Protein identification with mass spectrometric methods is a key step in modern proteomics studies. Some tools are available today for doing different steps in the analysis. Only a few commercial systems integrate all the steps in the analysis, often for only one vendor's hardware, and the details of these systems are not public.

Results: A complete system for doing protein identification with peptide mass fingerprints is presented, including everything from peak picking to matching the database protein. The details of the different algorithms are disclosed so that academic researchers can have full control of their tools.

Availability: The described software tools are available from the Halmstad University website www.hh.se/staff/bioinf/

Supplementary information: Details of the algorithms are described in supporting information available from the Halmstad University website www.hh.se/staff/bioinf/

* To whom correspondence should be addressed.


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