Predicting RNA secondary structure via adaptive deep recurrent neural networks with energy-based filter

BACKGROUND: RNA secondary structure prediction is an important issue in structural bioinformatics, and RNA pseudoknotted secondary structure prediction represents an NP-hard problem. Recently, many different machine-learning methods, Markov models, and neural networks have been employed for this pro...

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Detalles Bibliográficos
Autores principales: Lu, Weizhong, Tang, Ye, Wu, Hongjie, Huang, Hongmei, Fu, Qiming, Qiu, Jing, Li, Haiou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929275/
https://www.ncbi.nlm.nih.gov/pubmed/31874602
http://dx.doi.org/10.1186/s12859-019-3258-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929275/
https://www.ncbi.nlm.nih.gov/pubmed/31874602
http://dx.doi.org/10.1186/s12859-019-3258-7

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