Super.FELT: supervised feature extraction learning using triplet loss for drug response prediction with multi-omics data.

Park, Sejin; Soh, Jihee; Lee, Hyunju

Park, Sejin; Soh, Jihee; Lee, Hyunju.

Afiliação

Park S; School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea.
Soh J; School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea.
Lee H; School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea. hyunjulee@gist.ac.kr.

BMC Bioinformatics ; 22(1): 269, 2021 May 25.

Article em En | MEDLINE | ID: mdl-34034645

Assuntos

Fenômenos Biológicos; Neoplasias; Preparações Farmacêuticas; Humanos; Mutação; Medicina de Precisão

Palavras-chave

Drug response prediction; Multi-omics data; Pharmacogenomics; Precision oncology; Triplet loss; encoder using supervised methods

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fenômenos Biológicos / Preparações Farmacêuticas / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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