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

Samuelsson, J; Dalevi, D; Levander, Fredrik LU and Rognvaldsson, T (2004) In Bioinformatics1998-01-01+01:00 20(18). p.3628-3635
Abstract
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... (More)
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. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Bioinformatics1998-01-01+01:00
volume
20
issue
18
pages
3628 - 3635
publisher
Oxford University Press
external identifiers
  • wos:000225786600038
  • pmid:15297302
  • scopus:12344287002
ISSN
1367-4803
DOI
10.1093/bioinformatics/bth460
language
English
LU publication?
yes
id
7bf87a20-0bd7-4d61-a192-23db19dd2aed (old id 259047)
date added to LUP
2007-10-31 11:57:48
date last changed
2017-01-01 05:08:03
@article{7bf87a20-0bd7-4d61-a192-23db19dd2aed,
  abstract     = {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.},
  author       = {Samuelsson, J and Dalevi, D and Levander, Fredrik and Rognvaldsson, T},
  issn         = {1367-4803},
  language     = {eng},
  number       = {18},
  pages        = {3628--3635},
  publisher    = {Oxford University Press},
  series       = {Bioinformatics1998-01-01+01:00},
  title        = {Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting},
  url          = {http://dx.doi.org/10.1093/bioinformatics/bth460},
  volume       = {20},
  year         = {2004},
}