Results: In this work, we review six recent methods for tackling this problem with machine learning. We compare the models in five genome-wide ...

In this work, we review six recent methods for tackling this problem with machine learning. We compare the models in five genome-wide datasets.

Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning ; Journal: Briefings in Bioinformatics, 2020, № 3 ; Publisher: ...

Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning. ; Bugnon, Leandro A ; Yones, Cristian ; Milone, Diego H ...

This work provides a novel approach for dealing with the computational prediction of pre-miRNAs: a convolutional deep residual neural network (mirDNN).

Motivation: Although many machine learning techniques have been proposed for distinguishing miRNA hairpins from other stem-loop sequences, ...

For example, analyses of small RNA transcripts from human and chimpanzee brains more than doubled the number of known miRNA genes, and revealed a surprisingly ...

The computational approaches used for pre-miRNA identification may be divided into two groups: homology search methods and machine learning methods. The first ...

Oct 26, 2020 · This work provides a novel approach for dealing with the computational prediction of pre-miRNAs: a convolutional deep residual neural network.

Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning · Computer Science, Biology. Briefings Bioinform. · 2021.