Solving the RNA design problem with reinforcement learning

We use reinforcement learning to train an agent for computational RNA design: given a target secondary structure, design a sequence that folds to that structure in silico. Our agent uses a novel graph convolutional architecture allowing a single model to be applied to arbitrary target structures of...

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Detalles Bibliográficos
Autores principales: Eastman, Peter, Shi, Jade, Ramsundar, Bharath, Pande, Vijay S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029810/
https://www.ncbi.nlm.nih.gov/pubmed/29927936
http://dx.doi.org/10.1371/journal.pcbi.1006176

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029810/
https://www.ncbi.nlm.nih.gov/pubmed/29927936
http://dx.doi.org/10.1371/journal.pcbi.1006176

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