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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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| Pubblicato in: | BMC Bioinformatics |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
BioMed Central
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6929275/ https://ncbi.nlm.nih.gov/pubmed/31874602 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-019-3258-7 |
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