ReviewFrontiers in genetics2020
A Literature Review of Gene Function Prediction by Modeling Gene Ontology.
Review in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
44 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Meta-analysis of microarray data to identify potential signature genes and MiRNAs associated with the pathogenesis of asthma.Journal of translational medicine · 2025Pooled it
- MicroRNAs-mediated regulation of the differentiation of dental pulp-derived mesenchymal stem cells: a systematic review and bioinformatic analysis.Stem cell research & therapy · 2023Pooled it
- Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation.Molecular ecology · 2026Article
- Explainable machine learning-driven identification of heart failure biomarkers: a multi-model feature selection approach with SHAP-based interpretability.Scientific reports · 2026Article
- Article
- Go Big or go home: a new gene ontology subset that improves plant gene function prediction.Plant methods · 2026Article
- Evaluating network-based algorithms for protein function prediction using plant protein-protein interaction networks.BMC plant biology · 2026Article
- Functional Interpretation of Omics Data: From Pathways to Networks.Advances in experimental medicine and biology · 2026Review
- SeqExpressionAnalyser: An R Package for Automated End-to-End RNA-Seq Analysis From Reads to Differential Expression.Bioinformatics and biology insights · 2026Article
- Host-Derived Reactive Oxygen Species in the Gut Epithelium: Defence Mechanism and Target of Bacterial Subversion.Antioxidants (Basel, Switzerland) · 2025Review
- Study on the Degradation of Aflatoxin B1 byBiology · 2025Article
- New insights into the genomic information of an overlooked human pathogen: Bartonella rochalimae causative agent of Carrion's disease.PLoS neglected tropical diseases · 2025Article
- Clinical application and immune infiltration landscape of stemness-related genes in heart failure.ESC heart failure · 2025Article
- Influence of multi-species data on gene-disease associations in substance use disorder using random walk with restart models.PloS one · 2025Article
- Investigating the Activities ofBiology · 2024Article
- Microarray analysis points to LMNB1 and JUN as potential target genes for predicting metastasis promotion by etoposide in colorectal cancer.Scientific reports · 2024Article
- simona: a comprehensive R package for semantic similarity analysis on bio-ontologies.BMC genomics · 2024Article
- Fitness effects of synthetic and natural diet preservatives on the edible insect Bombyx mori.NPJ science of food · 2024Article
- PlasGO: enhancing GO-based function prediction for plasmid-encoded proteins based on genetic structure.GigaScience · 2024Article
- Translation of genome-wide association study: from genomic signals to biological insights.Frontiers in genetics · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.