Extracting functional insights from loss-of-function screens using deep link prediction.

Strybol, Pieter-Paul; Larmuseau, Maarten; de Schaetzen van Brienen, Louise; Van den Bulcke, Tim; Marchal, Kathleen

Strybol, Pieter-Paul; Larmuseau, Maarten; de Schaetzen van Brienen, Louise; Van den Bulcke, Tim; Marchal, Kathleen.

Afiliación

Strybol PP; Department of Plant Biotechnology and Bioinformatics, Department of Information Technology, IDLab, imec, iGent Toren, 9000 Gent, Belgium.
Larmuseau M; Department of Plant Biotechnology and Bioinformatics, Department of Information Technology, IDLab, imec, iGent Toren, 9000 Gent, Belgium.
de Schaetzen van Brienen L; Department of Plant Biotechnology and Bioinformatics, Department of Information Technology, IDLab, imec, iGent Toren, 9000 Gent, Belgium.
Van den Bulcke T; Galapagos NV, Generaal De Wittelaan L11 A3, 2800 Mechelen, Belgium.
Marchal K; Department of Plant Biotechnology and Bioinformatics, Department of Information Technology, IDLab, imec, iGent Toren, 9000 Gent, Belgium.

Cell Rep Methods ; 2(2): 100171, 2022 02 28.

Article en En | MEDLINE | ID: mdl-35474966

Asunto(s)

Neoplasias; Humanos; Neoplasias/genética; Interferencia de ARN; Línea Celular

Palabras clave

CRISPR screening; PPI networks; bioinformatics; cancer cell lines; deep learning; drug targets; functional screening; link prediction; machine learning; systems biology

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Cell Rep Methods Año: 2022 Tipo del documento: Article País de afiliación: Bélgica

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