Related Experiment Video
Updated: Jun 25, 2025
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Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells
Published on: March 24, 2023
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An Extendible Realism-Based Ontology for Kinship
Michael Rabenberg1, Anuwat Pengput1, Werner Ceusters1
1University at Buffalo, 77 Goodell Street, Buffalo NY, 14203, USA.
CEUR Workshop Proceedings
|May 29, 2024
Summary
This study introduces a novel kinship ontology aligned with the Basic Formal Ontology (BFO). It enhances medical and biomedical data by providing robust representation of family relationships and aiding in error detection.
Area of Science:
- Biomedical Informatics
- Ontology Engineering
- Medical Data Representation
Background:
- Accurate representation of kinship is vital for medical and biomedical applications.
- Existing kinship ontologies do not align with the Basic Formal Ontology (BFO) standards.
Purpose of the Study:
- To propose a novel kinship ontology that adheres to BFO principles.
- To improve the representation of kinship relations in biomedical contexts.
Main Methods:
- Developed a novel kinship ontology fully axiomatized in First Order Logic (FOL) following BFO2020-FOL rules.
- Modularized the ontology into 6 Common Logic Interface Format (CLIF) files for flexible import.
- Created bridging axioms for integration with SNOMED CT.
- Incorporated a module with specialized axioms for detecting unusual kinship relations and potential data entry errors.
Main Results:
- A novel, BFO-compliant kinship ontology has been developed.
- The ontology is modular, axiomatized in FOL, and interoperable with SNOMED CT.
- Includes a unique module for identifying and alerting on atypical kinship relationships.
Conclusions:
- The proposed kinship ontology offers a standardized and robust framework for representing family relationships in biomedical informatics.
- This ontology facilitates improved data accuracy and supports the identification of complex or erroneous kinship data.
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