Deep learning allows genome-scale prediction of Michaelis constants from structural features.

Kroll, Alexander; Engqvist, Martin K M; Heckmann, David; Lercher, Martin J

Kroll, Alexander; Engqvist, Martin K M; Heckmann, David; Lercher, Martin J.

Afiliação

Kroll A; Institute for Computer Science and Department of Biology, Heinrich Heine University, Düsseldorf, Germany.
Engqvist MKM; Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Heckmann D; Institute for Computer Science and Department of Biology, Heinrich Heine University, Düsseldorf, Germany.
Lercher MJ; Institute for Computer Science and Department of Biology, Heinrich Heine University, Düsseldorf, Germany.

PLoS Biol ; 19(10): e3001402, 2021 10.

Article em En | MEDLINE | ID: mdl-34665809

Assuntos

Aprendizado Profundo; Genoma; Bases de Dados Genéticas; Enzimas/metabolismo; Cinética; Metabolômica; Modelos Biológicos; Redes Neurais de Computação; Especificidade por Substrato

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma / Aprendizado Profundo Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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