ArticleDisease models & mechanisms2018
Disease Ontology: improving and unifying disease annotations across species.
Article in Disease models & mechanisms, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed.
- Mondo: integrating disease terminology across communities.Genetics · 2026Article
- theRNA: a curated knowledgebase of functional RNA therapeutics spanning diverse modalities and disease applications.Nucleic acids research · 2026Article
- Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.Renal failure · 2025Article
- Benchmarking Transformer Embedding Models for Biomedical Terminology Standardization.Machine learning with applications · 2025Article
- iPiDA-LGE: a local and global graph ensemble learning framework for identifying piRNA-disease associations.BMC biology · 2025Article
- IGF1 and CXCR4 Respectively Related With Inhibited M1 Macrophage Polarization in Keloids.The Journal of craniofacial surgery · 2024Article
- Quantifying the massive pleiotropy of microRNA: a human microRNA-disease causal association database generated with ChatGPT.bioRxiv : the preprint server for biology · 2024Article
- Homeostasis imbalance process ontology: a study on COVID-19 infectious processes.BMC medical informatics and decision making · 2024Article
- DiSMVC: a multi-view graph collaborative learning framework for measuring disease similarity.Bioinformatics (Oxford, England) · 2024Article
- Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction.BMC genomics · 2024Article
- Mycobacteriaceae Phenome Atlas (MPA): A Standardized Atlas for the Mycobacteriaceae Phenome Based on Heterogeneous Sources.Phenomics (Cham, Switzerland) · 2023Article
- Identification and analysis of lipid metabolism-related genes in allergic rhinitis.Lipids in health and disease · 2023Article
- Article
- Identification of ferroptosis related markers by integrated bioinformatics analysis and In vitro model experiments in rheumatoid arthritis.BMC medical genomics · 2023Article
- Integrated bioinformatic analysis of mitochondrial metabolism-related genes in acute myeloid leukemia.Frontiers in immunology · 2023Article
- H19 may regulate the immune cell infiltration in carcinogenesis of gastric cancer through miR-378a-5p/SERPINH1 signaling.World journal of surgical oncology · 2022Article
- Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque.Nature communications · 2022Article
- The Xenopus phenotype ontology: bridging model organism phenotype data to human health and development.BMC bioinformatics · 2022Article
- Mouse Genome Informatics (MGI): latest news from MGD and GXD.Mammalian genome : official journal of the International Mammalian Genome Society · 2022Article
- Identification of the Diagnostic Biomarker VIPR1 in Hepatocellular Carcinoma Based on Machine Learning Algorithm.Journal of oncology · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making comparisons and inferences difficult. A unified disease ontology is required that connects data annotated using diverse disease terminologies, and in which the terminology relationships are continuously maintained. The Mouse Genome Database (MGD, http://www.informatics.jax.org), Rat Genome Database (RGD, http://rgd.mcw.edu) and Disease Ontology (DO, http://www.disease-ontology.org) projects are collaborating to augment DO, aligning and incorporating disease terms used by MGD and RGD, and improving DO as a tool for unifying disease annotations across species. Coordinated assessment of MGD's and RGD's disease term annotations identified new terms that enhance DO's representation of human diseases. Expansion of DO term content and cross-references to clinical vocabularies (e.g. OMIM, ORDO, MeSH) has enriched the DO's domain coverage and utility for annotating many types of data generated from experimental and clinical investigations. The extension of anatomy-based DO classification structure of disease improves accessibility of terms and facilitates application of DO for computational research. A consistent representation of disease associations across data types from cellular to whole organism, generated from clinical and model organism studies, will promote the integration, mining and comparative analysis of these data. The coordinated enrichment of the DO and adoption of DO by MGD and RGD demonstrates DO's usability across human data, MGD, RGD and the rest of the model organism database community.
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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 Socratic graph.