Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers.

Tao, Yifeng; Ma, Xiaojun; Palmer, Drake; Schwartz, Russell; Lu, Xinghua; Osmanbeyoglu, Hatice Ulku

Tao, Yifeng; Ma, Xiaojun; Palmer, Drake; Schwartz, Russell; Lu, Xinghua; Osmanbeyoglu, Hatice Ulku.

Afiliación

Tao Y; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
Ma X; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Palmer D; UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA.
Schwartz R; UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA.
Lu X; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
Osmanbeyoglu HU; Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA.

Nucleic Acids Res ; 50(19): 10869-10881, 2022 10 28.

Article en En | MEDLINE | ID: mdl-36243974

Asunto(s)

Aprendizaje Profundo; Neoplasias; Humanos; Cromatina/genética; Neoplasias/genética; Medicina de Precisión; Factores de Transcripción/genética; Factores de Transcripción/metabolismo

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Neoplasias Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

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