BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria

Recent technological advances have led to an exponential expansion of biological sequence data and extraction of meaningful information through Machine Learning (ML) algorithms. This knowledge has improved the understanding of mechanisms related to several fatal diseases, e.g. Cancer and coronavirus...

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Detalles Bibliográficos
Autores principales: Bonidia, Robson P, Santos, Anderson P Avila, de Almeida, Breno L S, Stadler, Peter F, da Rocha, Ulisses N, Sanches, Danilo S, de Carvalho, André C P L F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Problem Solving Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294424/
https://www.ncbi.nlm.nih.gov/pubmed/35753697
http://dx.doi.org/10.1093/bib/bbac218

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294424/
https://www.ncbi.nlm.nih.gov/pubmed/35753697
http://dx.doi.org/10.1093/bib/bbac218

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