ArticleScientific data2026
A general strategy for generating expert-guided, simplified views of ontologies.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed.
- The Cell Ontology in the age of single-cell omics.Scientific data · 2026Article
- Chemical classification program synthesis using generative artificial intelligence.Journal of cheminformatics · 2025Article
- Construction, Deployment, and Usage of the Human Reference Atlas Knowledge Graph.Scientific data · 2025Article
- Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas construction and usage.Nature methods · 2025Article
- Digital evolution: Novo Nordisk's shift to ontology-based data management.Journal of biomedical semantics · 2025Article
- Construction, Deployment, and Usage of the Human Reference Atlas Knowledge Graph for Linked Open Data.bioRxiv : the preprint server for biology · 2025Article
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15 authors.
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Abstract
Annotation of biomedical entities with widely used, well-structured ontologies and ontology-aware tools ensures data and analyses are Findable, Accessible, Interoperable, and Reusable (FAIR). Standardized terms with synonyms support lexical search, while ontology structure enables biologically meaningful grouping of annotations, such as by location and type. However, ontologies serving diverse communities are often more complex than needed for specific applications, creating barriers to adoption by researchers and resource developers. For example, cell atlases often attempt simplifications by manually building term hierarchies linking to cell type and anatomy ontologies, but these may include relationship types unsuitable for grouping annotations. We present tools for validating human expert curated term hierarchies, developed in two human reference atlas projects, against ontology structures. The tools provide tabular statistics plus graphical views of matching and non-matching terms and relationships to support discussion and conflict resolution. The HuBMAP Human Reference Atlas (HRA) effort is used to validate the approach and tools, and the Human Developmental Cell Atlas is featured as a use case.
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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.