Biological network topology features predict gene dependencies in cancer cell-lines.

Benstead-Hume, Graeme; Wooller, Sarah K; Renaut, Joanna; Dias, Samantha; Woodbine, Lisa; Carr, Antony M; Pearl, Frances M G

Benstead-Hume, Graeme; Wooller, Sarah K; Renaut, Joanna; Dias, Samantha; Woodbine, Lisa; Carr, Antony M; Pearl, Frances M G.

Afiliação

Benstead-Hume G; Bioinformatics Lab, School of Life Sciences, University of Sussex, Brighton BN1 9QJ, UK.
Wooller SK; Division of Cancer Biology, The Institute of Cancer Research, London SW3 6JB, UK.
Renaut J; Bioinformatics Lab, School of Life Sciences, University of Sussex, Brighton BN1 9QJ, UK.
Dias S; Bioinformatics Lab, School of Life Sciences, University of Sussex, Brighton BN1 9QJ, UK.
Woodbine L; Genome Damage and Stability Centre, University of Sussex, Brighton BN1 9RQ, UK.
Carr AM; Genome Damage and Stability Centre, University of Sussex, Brighton BN1 9RQ, UK.
Pearl FMG; Genome Damage and Stability Centre, University of Sussex, Brighton BN1 9RQ, UK.

Bioinform Adv ; 2(1): vbac084, 2022.

Article em En | MEDLINE | ID: mdl-36699394

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Bioinform Adv Ano de publicação: 2022 Tipo de documento: Article

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