A systematic review of the application of machine learning in the detection and classification of transposable elements

BACKGROUND: Transposable elements (TEs) constitute the most common repeated sequences in eukaryotic genomes. Recent studies demonstrated their deep impact on species diversity, adaptation to the environment and diseases. Although there are many conventional bioinformatics algorithms for detecting an...

Descripción completa

Detalles Bibliográficos
Autores principales: Orozco-Arias, Simon, Isaza, Gustavo, Guyot, Romain, Tabares-Soto, Reinel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Bioinformatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6967008/
https://www.ncbi.nlm.nih.gov/pubmed/31976169
http://dx.doi.org/10.7717/peerj.8311

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6967008/
https://www.ncbi.nlm.nih.gov/pubmed/31976169
http://dx.doi.org/10.7717/peerj.8311

Ejemplares similares