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pyQms enables universal and accurate quantification of mass spectrometry data.
Leufken, Johannes; Niehues, Anna; Sarin, L Peter; Wessel, Florian; Hippler, Michael; Leidel, Sebastian A; Fufezan, Christian.
Afiliação
  • Leufken J; From the ‡Institute of Plant Biology and Biotechnology, University of Muenster, Schlossplatz 8, 48143 Muenster, Germany.
  • Niehues A; §Max Planck Research Group for RNA Biology, Max Planck Institute for Molecular Biomedicine, Von-Esmarch-Strasse 54, 48149 Muenster, Germany.
  • Sarin LP; From the ‡Institute of Plant Biology and Biotechnology, University of Muenster, Schlossplatz 8, 48143 Muenster, Germany.
  • Wessel F; §Max Planck Research Group for RNA Biology, Max Planck Institute for Molecular Biomedicine, Von-Esmarch-Strasse 54, 48149 Muenster, Germany.
  • Hippler M; From the ‡Institute of Plant Biology and Biotechnology, University of Muenster, Schlossplatz 8, 48143 Muenster, Germany.
  • Leidel SA; ¶Deutsches Krebsforschungszentrum, G181 DKFZ-Bayer Joint Immunotherapy Laboratory, 69120 Heidelberg, Germany.
  • Fufezan C; From the ‡Institute of Plant Biology and Biotechnology, University of Muenster, Schlossplatz 8, 48143 Muenster, Germany.
Mol Cell Proteomics ; 16(10): 1736-1745, 2017 10.
Article em En | MEDLINE | ID: mdl-28729385
ABSTRACT
Quantitative mass spectrometry (MS) is a key technique in many research areas (1), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here, we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching that offers an accurate quality assessment of all quantifications and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large scale and high throughput, the most challenging task for a quantification algorithm.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Proteoma / Espectrometria de Massas por Ionização por Electrospray / Proteômica / Espectrometria de Massas em Tandem / Marcação por Isótopo Tipo de estudo: Evaluation_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Proteoma / Espectrometria de Massas por Ionização por Electrospray / Proteômica / Espectrometria de Massas em Tandem / Marcação por Isótopo Tipo de estudo: Evaluation_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article