AIMC Topic: Biological Ontologies

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Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach.

PloS one
With the novel COVID-19 pandemic disrupting and threatening the lives of millions, researchers and clinicians have been recently conducting clinical trials at an unprecedented rate to learn more about the virus and potential drugs/treatments/vaccines...

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.

Nature reviews. Nephrology
An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medic...

Ontology and values anchor indigenous and grey nomenclatures: a case study in lichen naming practices among the Samí, Sherpa, Scots, and Okanagan.

Studies in history and philosophy of biological and biomedical sciences
Ethnobotanical research provides ample justification for comparing diverse biological nomenclatures and exploring ways that retain alternative naming practices. However, how (and whether) comparison of nomenclatures is possible remains a subject of d...

Ontological approach to the knowledge systematization of a toxic process and toxic course representation framework for early drug risk management.

Scientific reports
Various types of drug toxicity can halt the development of a drug. Because drugs are xenobiotics, they inherently have the potential to cause injury. Clarifying the mechanisms of toxicity to evaluate and manage drug safety during drug development is ...

Ontologies, Knowledge Representation, and Machine Learning for Translational Research: Recent Contributions.

Yearbook of medical informatics
OBJECTIVES: To select, present, and summarize the most relevant papers published in 2018 and 2019 in the field of Ontologies and Knowledge Representation, with a particular focus on the intersection between Ontologies and Machine Learning.

Structuring, reuse and analysis of electronic dental data using the Oral Health and Disease Ontology.

Journal of biomedical semantics
BACKGROUND: A key challenge for improving the quality of health care is to be able to use a common framework to work with patient information acquired in any of the health and life science disciplines. Patient information collected during dental care...

Identifying disease trajectories with predicate information from a knowledge graph.

Journal of biomedical semantics
BACKGROUND: Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses that identify e.g. relationships between diseases. Some diseases are often dia...

Biomedical Holistic Ontology for People with Rare Diseases.

International journal of environmental research and public health
This research provides a biomedical ontology to adequately represent the information necessary to manage a person with a disease in the context of a specific patient. A bottom-up approach was used to build the ontology, best ontology practices descri...