Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction.

Li, Yang; Zhang, Chengxin; Feng, Chenjie; Pearce, Robin; Lydia Freddolino, P; Zhang, Yang

Li, Yang; Zhang, Chengxin; Feng, Chenjie; Pearce, Robin; Lydia Freddolino, P; Zhang, Yang.

Afiliación

Li Y; Cancer Science Institute of Singapore, National University of Singapore, 117599, Singapore, Singapore.
Zhang C; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
Feng C; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
Pearce R; Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT, 06511, USA.
Lydia Freddolino P; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
Zhang Y; School of Science, Ningxia Medical University, Yinchuan, 750004, China.

Nat Commun ; 14(1): 5745, 2023 09 16.

Article en En | MEDLINE | ID: mdl-37717036

Asunto(s)

Bases de Datos de Ácidos Nucleicos; Aprendizaje; Conocimiento; ARN; Sistemas de Lectura

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Bases de Datos de Ácidos Nucleicos / Aprendizaje Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2023 Tipo del documento: Article País de afiliación: Singapur

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