Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology.
RNA sequencing
artificial intelligence
cancer heterogeneity
Journal
International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791
Informations de publication
Date de publication:
27 Apr 2021
27 Apr 2021
Historique:
received:
20
03
2021
revised:
21
04
2021
accepted:
23
04
2021
entrez:
30
4
2021
pubmed:
1
5
2021
medline:
4
6
2021
Statut:
epublish
Résumé
Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of precision medicine. Here, we provide an overview of artificial intelligence approaches for the analysis of large-scale RNA-sequencing datasets in cancer. We present the major solutions to disentangle inter- and intra-tumor heterogeneity of transcriptome profiles for an effective improvement of patient management. We outline the contributions of learning algorithms to the needs of cancer genomics, from identifying rare cancer subtypes to personalizing therapeutic treatments.
Identifiants
pubmed: 33925407
pii: ijms22094563
doi: 10.3390/ijms22094563
pmc: PMC8123853
pii:
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Associazione Italiana per la Ricerca sul Cancro
ID : MFAG 20566
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