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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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| Pubblicato in: | BMC Bioinformatics |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
BioMed Central
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5249014/ https://ncbi.nlm.nih.gov/pubmed/28105918 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-016-1343-8 |
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