ReviewDatabase : the journal of biological databases and curation2025
A review on Gene Ontology evaluations.
Review in Database : the journal of biological databases and curation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Genome-Wide Study of MYB Transcription Factors in Maize and Their Essential Roles in Male Fertility and Other Biological Processes.International journal of molecular sciences · 2026Article
- Large-Scale Comparative Genomics of European and Chinese Cattle Breeds Reveals Population Structure, Breeding History, and Adaptive Divergence.Animals : an open access journal from MDPI · 2026Article
- Secretory VSMC-derived THBS1 promotes macrophage M1 polarization and inflammation in intracranial aneurysms via the CD47/NF-κB axis.Frontiers in immunology · 2026Article
- Computational prioritization of candidate TCDD-associated targets in retinoblastoma using network toxicology and transcriptomic analysis.Frontiers in genetics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The analysis of the large and heterogeneous datasets that characterize modern biology demands systems capable of representing biological knowledge in a formal, standardized manner. The most widely used structured vocabulary in molecular biology and biomedicine is the Gene Ontology (GO). Although employed in many different data analysis tasks, its main application is in the functional annotation of gene products and the subsequent functional enrichment analysis of large gene/protein datasets derived from omics experiments. This key position in modern biology means the GO is subject to continuous scrutiny and improvement, not only by its developers but by the community in general. GO's vocabulary, structure, and gene annotations have been evaluated from multiple points of view, revealing important insights into how we organize our biological knowledge, the associated problems, and strategies for overcoming them. These evaluations range from technical analyses of its ontological architecture to assessments of its effectiveness in supporting biological research. This process ensures that this essential resource is updated and adapted to the new challenges posed by modern biology. In this review, we summarize some key evaluations that the GO has undergone over time.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.