ArticleNucleic acids research2020
The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 151 papers, 3 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
151 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Graph databases in systems biology: a systematic review.Briefings in bioinformatics · 2024Pooled it
- Classical cannabinoid receptors as target in cancer-induced bone pain: a systematic review, meta-analysis and bioinformatics validation.Scientific reports · 2024Pooled it
- Curation and expansion of Human Phenotype Ontology for defined groups of inborn errors of immunity.The Journal of allergy and clinical immunology · 2022Pooled it
- OMICON: a community resource for studying gene coexpression networks in normal and neoplastic human brain samples.bioRxiv : the preprint server for biology · 2026Article
- Systematic benchmarking demonstrates large language models have not reached the diagnostic accuracy of traditional rare-disease decision support tools.European journal of human genetics : EJHG · 2026Article
- Scientific knowledge graph and ontology generation using open large language models.Digital discovery · 2026Article
- RNA-KG v2.0: an RNA-centered Knowledge Graph with Properties.NAR genomics and bioinformatics · 2026Article
- A custom phenotypic profile for Fanconi anemia: Addressing gaps in existing disease annotations.medRxiv : the preprint server for health sciences · 2026Article
- A Co-Expressed Cluster of Genes in the Anterior Brain of Female Crickets Activated by a Species-Specific Calling Song.International journal of molecular sciences · 2026Article
- molIEreVIS: exploring and interpreting the evidence behind drug repurposing predictions.Frontiers in bioinformatics · 2026Article
- The future of fundamental science led by generative closed-loop artificial intelligence.Frontiers in artificial intelligence · 2026Review
- A multimodal vision knowledge graph of cardiovascular disease.Nature cardiovascular research · 2026Article
- Information content as a health system screening tool for rare diseases.NPJ digital medicine · 2025Article
- Large Language Models in Bio-Ontology Research: A Review.Bioengineering (Basel, Switzerland) · 2025Review
- A scalable approach for genomic-first rare disorder detection in a healthcare-based population.American journal of human genetics · 2025Article
- Development of self-phenotyping tools to empower patients and improve diagnostics.EBioMedicine · 2025Article
- Elucidating photoreceptor gene function with in-vivo CRISPR knock-out perturbation assay.Research square · 2025Article
- AgroLD: a knowledge graph for the plant sciences.BMC genomic data · 2025Article
- Creating an Interactive Web Interface for Networks Stored in Knowledge Graph Databases.Current protocols · 2025Article
- Harnessing genotype and phenotype data for population-scale variant classification using large language models and bayesian inference.Human genetics · 2025Article
91 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
59 authors.
Funding
Abstract
In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven't been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.
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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.