Genome-wide hairpins datasets of animals and plants for novel miRNA prediction

BUGNON, L.A.; YONES, C.; RAAD, J.; MILONE, D.H.; STEGMAYER, G.

Data in Brief

Elsevier

Lugar: Amsterdam; Año: 2019 vol. 25

2352-3409

This article makes available several genome-wide datasets, which can be used for training microRNA (miRNA) classifiers. The hairpin sequences available are from the genomes of: Homo sapiens, Arabidopsis thaliana, Anopheles gambiae, Caenorhabditis elegans and Drosophila melanogaster. Each dataset provides the genome data divided into sequences and a set of computed features for predictions. Each sequence has one label: i) ?positive?: meaning that it is a well-known pre-miRNA, according to miRBase v21; or ii) ?unlabeled?: indicating that the sequence has not (yet) a known function and could be a possible candidate to novel pre-miRNA. Due to the fact that selecting an informative feature set is very important for a good pre-miRNA classifier, a representative feature set with large discriminative power has been calculated and it is provided, as well, for each genome. This feature set contains typical information about sequence, topology and structure. Dataset was publically shared in https://sourceforge.net/projects/sourcesinc/files/mirdata/.