PhosphoSiteAnalyzer

A Bioinformatic Platform for Deciphering Phospho Proteomes Using Kinase Predictions Retrieved from NetworKIN

Martin V Bennetzen, Jürgen Cox, Matthias Mann, Jens S. Andersen

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

Phosphoproteomic experiments are routinely conducted in laboratories worldwide, and because of the fast development of mass spectrometric techniques and efficient phosphopeptide enrichment methods, researchers frequently end up having lists with tens of thousands of phosphorylation sites for further interrogation. To answer biologically relevant questions from these complex data sets, it becomes essential to apply computational, statistical, and predictive analytical methods. Here we provide an advanced bioinformatic platform termed "PhosphoSiteAnalyzer" to explore large phosphoproteomic data sets that have been subjected to kinase prediction using the previously published NetworKIN algorithm. NetworKIN applies sophisticated linear motif analysis and contextual network modeling to obtain kinase-substrate associations with high accuracy and sensitivity. PhosphoSiteAnalyzer provides an algorithm to retrieve kinase predictions from the public NetworKIN webpage in a semiautomated way and applies hereafter advanced statistics to facilitate a user-tailored in-depth analysis of the phosphoproteomic data sets. The interface of the software provides a high degree of analytical flexibility and is designed to be intuitive for most users. PhosphoSiteAnalyzer is a freeware program available at http://phosphosite.sourceforge.net .
OriginalsprogEngelsk
TidsskriftJournal of Proteome Research
Vol/bind11
Udgave nummer6
Sider (fra-til)3480-3486
ISSN1535-3893
DOI
StatusUdgivet - 2012

Fingeraftryk

Proteome
Bioinformatics
Computational Biology
Phosphotransferases
Phosphopeptides
Phosphorylation
Research Personnel
Statistics
Substrates
Datasets
Experiments

Citer dette

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abstract = "Phosphoproteomic experiments are routinely conducted in laboratories worldwide, and because of the fast development of mass spectrometric techniques and efficient phosphopeptide enrichment methods, researchers frequently end up having lists with tens of thousands of phosphorylation sites for further interrogation. To answer biologically relevant questions from these complex data sets, it becomes essential to apply computational, statistical, and predictive analytical methods. Here we provide an advanced bioinformatic platform termed {"}PhosphoSiteAnalyzer{"} to explore large phosphoproteomic data sets that have been subjected to kinase prediction using the previously published NetworKIN algorithm. NetworKIN applies sophisticated linear motif analysis and contextual network modeling to obtain kinase-substrate associations with high accuracy and sensitivity. PhosphoSiteAnalyzer provides an algorithm to retrieve kinase predictions from the public NetworKIN webpage in a semiautomated way and applies hereafter advanced statistics to facilitate a user-tailored in-depth analysis of the phosphoproteomic data sets. The interface of the software provides a high degree of analytical flexibility and is designed to be intuitive for most users. PhosphoSiteAnalyzer is a freeware program available at http://phosphosite.sourceforge.net .",
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PhosphoSiteAnalyzer : A Bioinformatic Platform for Deciphering Phospho Proteomes Using Kinase Predictions Retrieved from NetworKIN. / Bennetzen, Martin V; Cox, Jürgen; Mann, Matthias; Andersen, Jens S.

I: Journal of Proteome Research, Bind 11, Nr. 6, 2012, s. 3480-3486.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

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AU - Bennetzen, Martin V

AU - Cox, Jürgen

AU - Mann, Matthias

AU - Andersen, Jens S.

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AB - Phosphoproteomic experiments are routinely conducted in laboratories worldwide, and because of the fast development of mass spectrometric techniques and efficient phosphopeptide enrichment methods, researchers frequently end up having lists with tens of thousands of phosphorylation sites for further interrogation. To answer biologically relevant questions from these complex data sets, it becomes essential to apply computational, statistical, and predictive analytical methods. Here we provide an advanced bioinformatic platform termed "PhosphoSiteAnalyzer" to explore large phosphoproteomic data sets that have been subjected to kinase prediction using the previously published NetworKIN algorithm. NetworKIN applies sophisticated linear motif analysis and contextual network modeling to obtain kinase-substrate associations with high accuracy and sensitivity. PhosphoSiteAnalyzer provides an algorithm to retrieve kinase predictions from the public NetworKIN webpage in a semiautomated way and applies hereafter advanced statistics to facilitate a user-tailored in-depth analysis of the phosphoproteomic data sets. The interface of the software provides a high degree of analytical flexibility and is designed to be intuitive for most users. PhosphoSiteAnalyzer is a freeware program available at http://phosphosite.sourceforge.net .

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