Domain-adaptive neural networks improve cross-species prediction of transcription factor binding.

Cochran, Kelly; Srivastava, Divyanshi; Shrikumar, Avanti; Balsubramani, Akshay; Hardison, Ross C; Kundaje, Anshul; Mahony, Shaun

Cochran, Kelly; Srivastava, Divyanshi; Shrikumar, Avanti; Balsubramani, Akshay; Hardison, Ross C; Kundaje, Anshul; Mahony, Shaun.

Afiliación

Cochran K; Center for Eukaryotic Gene Regulation, Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Srivastava D; Department of Computer Science, Stanford University, Stanford, California 94305, USA.
Shrikumar A; Center for Eukaryotic Gene Regulation, Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Balsubramani A; Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Hardison RC; Department of Computer Science, Stanford University, Stanford, California 94305, USA.
Kundaje A; Department of Genetics, Stanford University, Stanford, California 94305, USA.
Mahony S; Center for Eukaryotic Gene Regulation, Pennsylvania State University, University Park, Pennsylvania 16802, USA.

Genome Res ; 32(3): 512-523, 2022 03.

Article en En | MEDLINE | ID: mdl-35042722

Asunto(s)

Redes Neurales de la Computación; Factores de Transcripción; Sitios de Unión; Secuenciación de Inmunoprecipitación de Cromatina; Biología Computacional/métodos; Unión Proteica; Factores de Transcripción/metabolismo

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Factores de Transcripción / Redes Neurales de la Computación Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Genome Res Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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