ReviewClinical and translational science2022
Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science.
Review in Clinical and translational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.
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
64 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Graph databases in systems biology: a systematic review.Briefings in bioinformatics · 2024Pooled it
- Perspectives on ionizing radiation and Parkinson's disease.NPJ Parkinson's disease · 2026Review
- Unlocking the Power of Data Harmonization in Environmental Health Sciences: A Comprehensive Exploration of Significance, Use Cases, and Recommendations for Standardization Efforts.Environmental health perspectives · 2026Review
- MetagenomicKG: a knowledge graph for metagenomic applications.Bioinformatics (Oxford, England) · 2026Article
- The ROBOKOP v1.0 knowledge graph system for exploring relationships between biomedical entities.Scientific reports · 2026Article
- Beyond Identifier Matching: An Empirical Characterization of Failure Modes in Biomedical Knowledge Graph Integration.medRxiv : the preprint server for health sciences · 2026Article
- AI and network biology for rational polypharmacology in signaling drug design: a review.NPJ precision oncology · 2026Review
- A layered standards framework for integrating single-cell and spatial omics data into brain cell atlases.bioRxiv : the preprint server for biology · 2026Article
- Knowledge Graph-Driven AI in Biohealth: From Biomedical Discovery to Health Risk Prediction.Delaware journal of public health · 2026Article
- SPHN Connector - a scalable pipeline for generating validated knowledge graphs from federated and semantically enriched health data.BMC medical informatics and decision making · 2026Article
- LinkML: an open data modeling framework.GigaScience · 2026Article
- KG-Microbe: Building modular and scalable knowledge graphs for microbiome and microbial sciences.GigaScience · 2026Article
- Federated knowledge retrieval elevates large language model performance on biomedical benchmarks.GigaScience · 2026Article
- Desiderata for a biomedical knowledge network: opportunities, challenges and future directions.Bioinformatics advances · 2026Article
- A Perspective on Software Intelligence for Autonomous Transformations in Biomedical Data and Knowledge.Learning health systems · 2026Article
- Protein Design Enters the Artificial Intelligence Era: Foundations, Tools, and Emerging Paradigms.Computational and structural biotechnology journal · 2026Review
- Large Language Models in Bio-Ontology Research: A Review.Bioengineering (Basel, Switzerland) · 2025Review
- monarchr: an R package for querying biomedical knowledge graphs.Bioinformatics (Oxford, England) · 2025Article
- Desiderata for a biomedical knowledge network: opportunities, challenges and future Directions.ArXiv · 2025Article
- Article
4 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors.
Funding
Abstract
Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph-based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these "knowledge graphs" (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open-access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open-source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object-oriented classification and graph-oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.
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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.