ArticleJMIR medical informatics2021
A Biomedical Knowledge Graph System to Propose Mechanistic Hypotheses for Real-World Environmental Health Observations: Cohort Study and Informatics Application.
Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 19 citations in OpenAlex.
- The ROBOKOP v1.0 knowledge graph system for exploring relationships between biomedical entities.Scientific reports · 2026Article
- Large Language Models in Bio-Ontology Research: A Review.Bioengineering (Basel, Switzerland) · 2025Review
- A review on knowledge graphs for healthcare: Resources, applications, and promises.Journal of biomedical informatics · 2025Review
- The Six Ds of Exponentials and drug discovery: A path toward reversing Eroom's law.Drug discovery today · 2025Review
- Connecting electronic health records to a biomedical knowledge graph to link clinical phenotypes and molecular endotypes in atopic dermatitis.Scientific reports · 2025Article
- BioBricks.ai: a versioned data registry for life sciences data assets.Frontiers in artificial intelligence · 2025Article
- Elucidating the mechanistic relationships between peroxisome proliferator-activated receptors and hepatic fibrosis using the ROBOKOP knowledge graph.Frontiers in toxicology · 2025Article
- An exploration of knowledge-organizing technologies to advance transdisciplinary back pain research.JOR spine · 2023Article
- BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs.Bioinformatics (Oxford, England) · 2023Article
- Cohort Network: A Knowledge Graph toward Data Dissemination and Knowledge-Driven Discovery for Cohort Studies.Environmental science & technology · 2023Article
- Lessons learned to enable question answering on knowledge graphs extracted from scientific publications: A case study on the coronavirus literature.Journal of biomedical informatics · 2023Article
- Article
- RTX-KG2: a system for building a semantically standardized knowledge graph for translational biomedicine.BMC bioinformatics · 2022Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundKnowledge graphs are a common form of knowledge representation in biomedicine and many other fields. We developed an open biomedical knowledge graph-based system termed Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP). ROBOKOP consists of both a front-end user interface and a back-end knowledge graph. The ROBOKOP user interface allows users to posit questions and explore answer subgraphs. Users can also posit questions through direct Cypher query of the underlying knowledge graph, which currently contains roughly 6 million nodes or biomedical entities and 140 million edges or predicates describing the relationship between nodes, drawn from over 30 curated data sources.
objectiveWe aimed to apply ROBOKOP to survey data on workplace exposures and immune-mediated diseases from the Environmental Polymorphisms Registry (EPR) within the National Institute of Environmental Health Sciences.
methodsWe analyzed EPR survey data and identified 45 associations between workplace chemical exposures and immune-mediated diseases, as self-reported by study participants (n= 4574), with 20 associations significant at P<.05 after false discovery rate correction. We then used ROBOKOP to (1) validate the associations by determining whether plausible connections exist within the ROBOKOP knowledge graph and (2) propose biological mechanisms that might explain them and serve as hypotheses for subsequent testing. We highlight the following three exemplar associations: carbon monoxide-multiple sclerosis, ammonia-asthma, and isopropanol-allergic disease.
resultsROBOKOP successfully returned answer sets for three queries that were posed in the context of the driving examples. The answer sets included potential intermediary genes, as well as supporting evidence that might explain the observed associations.
conclusionsWe demonstrate real-world application of ROBOKOP to generate mechanistic hypotheses for associations between workplace chemical exposures and immune-mediated diseases. We expect that ROBOKOP will find broad application across many biomedical fields and other scientific disciplines due to its generalizability, speed to discovery and generation of mechanistic hypotheses, and open nature.
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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.