Correction: Model performance and interpretability of semi-supervised generative adversarial networks to predict oncogenic variants with unlabeled data.

Ren, Zilin; Li, Quan; Cao, Kajia; Li, Marilyn M; Zhou, Yunyun; Wang, Kai

Ren, Zilin; Li, Quan; Cao, Kajia; Li, Marilyn M; Zhou, Yunyun; Wang, Kai.

Afiliação

Ren Z; Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Li Q; Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Cao K; Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON, M5G2C1, Canada.
Li MM; Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Zhou Y; Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Wang K; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.

BMC Bioinformatics ; 23(Suppl 3): 572, 2023 May 31.

Article em En | MEDLINE | ID: mdl-37259034

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google