ReviewBriefings in bioinformatics2021
Semantic similarity and machine learning with ontologies.
Review in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Katalyst: knowledge-guided semantic alignment via contrastive learning for enzyme turnover prediction.Bioinformatics (Oxford, England) · 2026Article
- A text mining and ontology-based approach using phenotypes to obtain relevant literature for rare diseases.iScience · 2026Article
- The role of protein embeddings for protein-protein interaction prediction with graph neural networks.Briefings in bioinformatics · 2026Article
- The Cell Ontology in the age of single-cell omics.Scientific data · 2026Article
- Article
- Pathway Analysis Interpretation in the Multi-Omic Era.Biotech (Basel (Switzerland)) · 2025Review
- The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients.Scientific reports · 2025Article
- Gene expression knowledge graph for patient representation and diabetes prediction.Journal of biomedical semantics · 2025Article
- Heterogeneous graph neural networks for link prediction in biomedical networks.Bioinformatics advances · 2025Review
- Advancing human health risk assessment: the role of new approach methodologies.Frontiers in toxicology · 2025Review
- Evaluation of a text-mining application for the rapid analysis of free-text wildlife necropsy reports.PloS one · 2025Article
- LCRAnnotationsDB: a database of low complexity regions functional and structural annotations.BMC genomics · 2024Article
- Unveiling inter-embryo variability in spindle length over time: Towards quantitative phenotype analysis.PLoS computational biology · 2024Article
- An ontology-based tool for modeling and documenting events in neurosurgery.BMC medical informatics and decision making · 2024Article
- Predicting gene disease associations with knowledge graph embeddings for diseases with curtailed information.NAR genomics and bioinformatics · 2024Article
- Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning.Bioinformatics (Oxford, England) · 2024Article
- Data-Driven Hypothesis Generation in Clinical Research: What We Learned from a Human Subject Study?Medical research archives · 2024Article
- From Food to Clinic: Mapping FoodOn to the UMLS to Enable Nutritional Decision Support.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Early detection of mild cognitive impairment through neuropsychological tests in population screenings: a decision support system integrating ontologies and machine learning.Frontiers in neuroinformatics · 2024Article
- Interpreting and visualizing pathway analyses using embedding representations with PAVER.Bioinformation · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ontologies have long been employed in the life sciences to formally represent and reason over domain knowledge and they are employed in almost every major biological database. Recently, ontologies are increasingly being used to provide background knowledge in similarity-based analysis and machine learning models. The methods employed to combine ontologies and machine learning are still novel and actively being developed. We provide an overview over the methods that use ontologies to compute similarity and incorporate them in machine learning methods; in particular, we outline how semantic similarity measures and ontology embeddings can exploit the background knowledge in ontologies and how ontologies can provide constraints that improve machine learning models. The methods and experiments we describe are available as a set of executable notebooks, and we also provide a set of slides and additional resources at https://github.com/bio-ontology-research-group/machine-learning-with-ontologies.
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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.