Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches.

Güvenç Paltun, Betül; Mamitsuka, Hiroshi; Kaski, Samuel

Güvenç Paltun, Betül; Mamitsuka, Hiroshi; Kaski, Samuel.

Güvenç Paltun B; Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Helsinki, Finland.
Mamitsuka H; Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan.
Kaski S; Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan.

Brief Bioinform ; 22(1): 346-359, 2021 01 18.

Article en En | MEDLINE | ID: mdl-31838491

Asunto(s)

Resistencia a Antineoplásicos; Genómica/métodos; Medicina de Precisión/métodos; Humanos; Aprendizaje Automático; Variantes Farmacogenómicas

Palabras clave

bioinformatics; drug response prediction; heterogeneous data integration; machine learning; personalized medicine

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Resistencia a Antineoplásicos / Genómica / Medicina de Precisión Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article

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