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The Mass Distance Fingerprint: A statistical framework for de novo detection of predominant modifications using high-accuracy mass spectrometry

Potthast, Frank; Gerrits, Bertran; Häkkinen, Jari LU ; Rutishauser, Dorothea; Ahrens, Christian H.; Roschitzki, Bernd; Baerenfaller, Katja; Munton, Richard P.; Walther, Pascal and Gehrig, Peter, et al. (2007) In Journal of Chromatography. B 854(1-2). p.173-182
Abstract
We describe a statistical measure, Mass Distance Fingerprint, for automatic de novo detection of predominant peptide mass distances, i.e., putative protein modifications. The method's focus is to globally detect mass differences, not to assign peptide sequences or modifications to individual spectra. The Mass Distance Fingerprint is calculated from high accuracy measured peptide masses. For the data sets used in this study, known mass differences are detected at electron mass accuracy or better. The proposed method is novel because it works independently of protein sequence databases and without any prior knowledge about modifications. Both modified and unmodified peptides have to be present in the sample to be detected. The method can be... (More)
We describe a statistical measure, Mass Distance Fingerprint, for automatic de novo detection of predominant peptide mass distances, i.e., putative protein modifications. The method's focus is to globally detect mass differences, not to assign peptide sequences or modifications to individual spectra. The Mass Distance Fingerprint is calculated from high accuracy measured peptide masses. For the data sets used in this study, known mass differences are detected at electron mass accuracy or better. The proposed method is novel because it works independently of protein sequence databases and without any prior knowledge about modifications. Both modified and unmodified peptides have to be present in the sample to be detected. The method can be used for automated detection of chemical/post-translational modifications, quality control of experiments and labeling approaches, and to control the modification settings of protein identification tools. The algorithm is implemented as a web application and is distributed as open source software. (Less)
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Contribution to journal
publication status
published
subject
keywords
modification, Mass Distance Histogram, post-translational, protein identification, Mass Distance Fingerprint
in
Journal of Chromatography. B
volume
854
issue
1-2
pages
173 - 182
publisher
Elsevier
external identifiers
  • wos:000248161900026
  • scopus:34250702089
ISSN
1873-376X
DOI
10.1016/j.jchromb.2007.04.020
language
English
LU publication?
yes
id
4d5185a7-e551-43da-95eb-22ad8b579a8b (old id 691784)
date added to LUP
2007-12-14 09:25:10
date last changed
2017-02-05 03:33:49
@article{4d5185a7-e551-43da-95eb-22ad8b579a8b,
  abstract     = {We describe a statistical measure, Mass Distance Fingerprint, for automatic de novo detection of predominant peptide mass distances, i.e., putative protein modifications. The method's focus is to globally detect mass differences, not to assign peptide sequences or modifications to individual spectra. The Mass Distance Fingerprint is calculated from high accuracy measured peptide masses. For the data sets used in this study, known mass differences are detected at electron mass accuracy or better. The proposed method is novel because it works independently of protein sequence databases and without any prior knowledge about modifications. Both modified and unmodified peptides have to be present in the sample to be detected. The method can be used for automated detection of chemical/post-translational modifications, quality control of experiments and labeling approaches, and to control the modification settings of protein identification tools. The algorithm is implemented as a web application and is distributed as open source software.},
  author       = {Potthast, Frank and Gerrits, Bertran and Häkkinen, Jari and Rutishauser, Dorothea and Ahrens, Christian H. and Roschitzki, Bernd and Baerenfaller, Katja and Munton, Richard P. and Walther, Pascal and Gehrig, Peter and Seif, Philipp and Seebergerg, Peter H. and Schlapbach, Ralph},
  issn         = {1873-376X},
  keyword      = {modification,Mass Distance Histogram,post-translational,protein identification,Mass Distance Fingerprint},
  language     = {eng},
  number       = {1-2},
  pages        = {173--182},
  publisher    = {Elsevier},
  series       = {Journal of Chromatography. B},
  title        = {The Mass Distance Fingerprint: A statistical framework for de novo detection of predominant modifications using high-accuracy mass spectrometry},
  url          = {http://dx.doi.org/10.1016/j.jchromb.2007.04.020},
  volume       = {854},
  year         = {2007},
}