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RIPPER: a framework for MS1 only metabolomics and proteomics label-free relative quantification.
Van Riper, Susan K; Higgins, LeeAnn; Carlis, John V; Griffin, Timothy J.
Afiliación
  • Van Riper SK; Department of Biomedical Informatics and Computational Biology, University of Minnesota, Rochester University of Minnesota Informatics Institute, University of Minnesota, St Paul.
  • Higgins L; Department of Biochemistry, Molecular Biology, and Biophysics.
  • Carlis JV; Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
  • Griffin TJ; Department of Biochemistry, Molecular Biology, and Biophysics.
Bioinformatics ; 32(13): 2035-7, 2016 07 01.
Article en En | MEDLINE | ID: mdl-27153682
UNLABELLED: RIPPER is a framework for mass-spectrometry-based label-free relative quantification for proteomics and metabolomics studies. RIPPER combines a series of previously described algorithms for pre-processing, analyte quantification, retention time alignment, and analyte grouping across runs. It is also the first software framework to implement proximity-based intensity normalization. RIPPER produces lists of analyte signals with their unnormalized and normalized intensities that can serve as input to statistical and directed mass spectrometry (MS) methods for detecting quantitative differences between biological samples using MS. AVAILABILITY AND IMPLEMENTATION: http://www.z.umn.edu/ripper CONTACT: vanr0014@umn.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Espectrometría de Masas / Programas Informáticos / Proteómica / Metabolómica Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2016 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Espectrometría de Masas / Programas Informáticos / Proteómica / Metabolómica Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2016 Tipo del documento: Article
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