DiagnoProt: a tool for discovery of new molecules by mass spectrometry.

Autor:	Silva ARF; Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil., Lima DB; Institut Pasteur, Structural Mass Spectrometry and Proteomics Unit, Paris, France., Leyva A; Analytical Biochemistry and Proteomics Unit, Institut Pasteur de Montevideo/IIBCE, Montevideo, Uruguay., Duran R; Analytical Biochemistry and Proteomics Unit, Institut Pasteur de Montevideo/IIBCE, Montevideo, Uruguay., Batthyany C; Analytical Biochemistry and Proteomics Unit, Institut Pasteur de Montevideo/IIBCE, Montevideo, Uruguay., Aquino PF; Leônidas and Maria Deane Institute, Fiocruz, Amazonas, Brazil., Leal JC; Leônidas and Maria Deane Institute, Fiocruz, Amazonas, Brazil., Rodriguez JE; Proteomics Unit, Chemistry Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil., Domont GB; Proteomics Unit, Chemistry Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil., Santos MDM; Carlos Chagas Institute, Computational Mass Spectrometry & Proteomics Group, Fiocruz, Paraná, Brazil., Chamot-Rooke J; Institut Pasteur, Structural Mass Spectrometry and Proteomics Unit, Paris, France., Barbosa VC; Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil., Carvalho PC; Carlos Chagas Institute, Computational Mass Spectrometry & Proteomics Group, Fiocruz, Paraná, Brazil.; Laboratory for Toxinology, Fiocruz, Rio de Janeiro, Brazil.
Jazyk:	angličtina
Zdroj:	Bioinformatics (Oxford, England) [Bioinformatics] 2017 Jun 15; Vol. 33 (12), pp. 1883-1885.
DOI:	10.1093/bioinformatics/btx093
Abstrakt:	Motivation: Around 75% of all mass spectra remain unidentified by widely adopted proteomic strategies. We present DiagnoProt, an integrated computational environment that can efficiently cluster millions of spectra and use machine learning to shortlist high-quality unidentified mass spectra that are discriminative of different biological conditions. Results: We exemplify the use of DiagnoProt by shortlisting 4366 high-quality unidentified tandem mass spectra that are discriminative of different types of the Aspergillus fungus. Availability and Implementation: DiagnoProt, a demonstration video and a user tutorial are available at http://patternlabforproteomics.org/diagnoprot . Contact: andrerfsilva@gmail.com or paulo@pcarvalho.com. Supplementary Information: Supplementary data are available at Bioinformatics online. (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com)
Databáze:	MEDLINE
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