Machine learning technology in the application of genome analysis: A systematic review.
Bioinformatics
Gene
Genomics
Machine learning
Journal
Gene
ISSN: 1879-0038
Titre abrégé: Gene
Pays: Netherlands
ID NLM: 7706761
Informations de publication
Date de publication:
15 Jul 2019
15 Jul 2019
Historique:
received:
24
01
2019
revised:
17
04
2019
accepted:
22
04
2019
pubmed:
27
4
2019
medline:
14
6
2019
entrez:
27
4
2019
Statut:
ppublish
Résumé
Machine learning (ML) is a powerful technique to tackle many problems in data mining and predictive analytics. We believe that ML will be of considerable potentials in the field of bioinformatics since the high-throughput technology is producing ever increasing biological data. In this review, we summarized major ML algorithms and conditions that must be paid attention to when applying these algorithms to genomic problems in details and we provided a list of examples from different perspectives and data analysis challenges at present.
Identifiants
pubmed: 31026571
pii: S0378-1119(19)30420-2
doi: 10.1016/j.gene.2019.04.062
pii:
doi:
Types de publication
Journal Article
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
149-156Informations de copyright
Copyright © 2019 Elsevier B.V. All rights reserved.