Improving SWATH-MS analysis by deep-learning.

Sun, Bo; Smialowski, Pawel; Aftab, Wasim; Schmidt, Andreas; Forne, Ignasi; Straub, Tobias; Imhof, Axel

Sun, Bo; Smialowski, Pawel; Aftab, Wasim; Schmidt, Andreas; Forne, Ignasi; Straub, Tobias; Imhof, Axel.

Afiliação

Sun B; Faculty of Medicine, Biomedical Center, Protein Analysis Unit, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
Smialowski P; Institute of Stem Cell Research, Helmholtz Center Munich, German Research Center for Environmental Health, Germany.
Aftab W; Faculty of Medicine, Biomedical Center, Computational Biology Unit, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
Schmidt A; Faculty of Medicine, Biomedical Center, Protein Analysis Unit, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
Forne I; Faculty of Medicine, Biomedical Center, Protein Analysis Unit, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
Straub T; Faculty of Medicine, Biomedical Center, Protein Analysis Unit, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
Imhof A; Faculty of Medicine, Biomedical Center, Computational Biology Unit, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.

Proteomics ; 23(9): e2200179, 2023 05.

Article em En | MEDLINE | ID: mdl-36571325

Assuntos

Aprendizado Profundo; Espectrometria de Massas em Tandem/métodos; Proteínas; Algoritmos; Bases de Dados Factuais

Palavras-chave

data independent acquisition; deep learning; proteomics; spectral Library

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Idioma: En Revista: Proteomics Assunto da revista: BIOQUIMICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha

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