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Fast mass spectrometry search and clustering of untargeted metabolomics data.
Mongia, Mihir; Yasaka, Tyler M; Liu, Yudong; Guler, Mustafa; Lu, Liang; Bhagwat, Aditya; Behsaz, Bahar; Wang, Mingxun; Dorrestein, Pieter C; Mohimani, Hosein.
Afiliação
  • Mongia M; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Yasaka TM; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Liu Y; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Guler M; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Lu L; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Bhagwat A; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Behsaz B; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Wang M; Chemia Biosciences Inc., Pittsburgh, PA, USA.
  • Dorrestein PC; Computer Science and Engineering, University of California Riverside, Riverside, CA, USA.
  • Mohimani H; Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA.
Nat Biotechnol ; 2024 Jan 02.
Article em En | MEDLINE | ID: mdl-38168990
ABSTRACT
The throughput of mass spectrometers and the amount of publicly available metabolomics data are growing rapidly, but analysis tools such as molecular networking and Mass Spectrometry Search Tool do not scale to searching and clustering billions of mass spectral data in metabolomics repositories. To address this limitation, we designed MASST+ and Networking+, which can process datasets that are up to three orders of magnitude larger than those processed by state-of-the-art tools.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Nat Biotechnol / Nat. biotechnol / Nature biotechnology Assunto da revista: BIOTECNOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Nat Biotechnol / Nat. biotechnol / Nature biotechnology Assunto da revista: BIOTECNOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos