Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction

BACKGROUND: MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still...

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Detalles Bibliográficos
Autores principales: Marques, Yuri Bento, de Paiva Oliveira, Alcione, Ribeiro Vasconcelos, Ana Tereza, Cerqueira, Fabio Ribeiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5249014/
https://www.ncbi.nlm.nih.gov/pubmed/28105918
http://dx.doi.org/10.1186/s12859-016-1343-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5249014/
https://www.ncbi.nlm.nih.gov/pubmed/28105918
http://dx.doi.org/10.1186/s12859-016-1343-8

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