A Literature Review of Gene Function Prediction by Modeling Gene Ontology.
directed acyclic graph
functional genomics
gene function prediction
gene ontology
inter-relationships
semantic similarity
Journal
Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621
Informations de publication
Date de publication:
2020
2020
Historique:
received:
02
01
2020
accepted:
30
03
2020
entrez:
12
5
2020
pubmed:
12
5
2020
medline:
12
5
2020
Statut:
epublish
Résumé
Annotating the functional properties of gene products, i.e., RNAs and proteins, is a fundamental task in biology. The Gene Ontology database (GO) was developed to systematically describe the functional properties of gene products across species, and to facilitate the computational prediction of gene function. As GO is routinely updated, it serves as the gold standard and main knowledge source in functional genomics. Many gene function prediction methods making use of GO have been proposed. But no literature review has summarized these methods and the possibilities for future efforts from the perspective of GO. To bridge this gap, we review the existing methods with an emphasis on recent solutions. First, we introduce the conventions of GO and the widely adopted evaluation metrics for gene function prediction. Next, we summarize current methods of gene function prediction that apply GO in different ways, such as using hierarchical or flat inter-relationships between GO terms, compressing massive GO terms and quantifying semantic similarities. Although many efforts have improved performance by harnessing GO, we conclude that there remain many largely overlooked but important topics for future research.
Identifiants
pubmed: 32391061
doi: 10.3389/fgene.2020.00400
pmc: PMC7193026
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
400Informations de copyright
Copyright © 2020 Zhao, Wang, Chen, Zhang, Guo and Yu.
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