PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data
Open accessAbstract
Disease ontologies facilitate the semantic organization and representation of domain-specific knowledge. In the case of prostate cancer (PCa), large volumes of research results and clinical data have been accumulated and needed to be standardized for sharing and translational researches. A formal representation of PCa-associated knowledge will be essential to the diverse data standardization, data sharing and the future knowledge graph extraction, deep phenotyping and explainable artificial intelligence developing. In this study, we constructed an updated PCa ontology (PCAO2) based on the ontology development life cycle. An online information retrieval system was designed to ensure the usability of the ontology. The PCAO2 with a subclass-based taxonomic hierarchy covers the major biomedical concepts for PCa-associated genotypic, phenotypic and lifestyle data. The current version of the PCAO2 contains 633 concepts organized under three biomedical viewpoints, namely, epidemiology, diagnosis and treatment. These concepts are enriched by the addition of definition, synonym, relationship and reference. For the precision diagnosis and treatment, the PCa-associated genes and lifestyles are integrated in the viewpoint of epidemiological aspects of PCa. PCAO2 provides a standardized and systematized semantic framework for studying large amounts of heterogeneous PCa data and knowledge, which can be further, edited and enriched by the scientific community. The PCAO2 is freely available at https://bioportal.bioontology.org/ontologies/PCAO, http://pcaontology.net/ and http://pcaontology.net/mobile/.
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- Authors
- Yu, C., Zong, H., Chen, Y., Zhou, Y., Liu, X., Lin, Y., Li, J., Zheng, X., Min, H., & Shen, B.
- Affiliations
- Sichuan University (CN)
- Nantong University (CN)
- Second Affiliated Hospital of Soochow University (CN)
- First Affiliated Hospital of Soochow University (CN)
- George Mason University (US)
- Corresponding author
- Min, Hua
- Shen, Bairong
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2024-03-27
- Volume
- 25
- Issue
- 3
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- PMC
- PMC10982949
- OpenAlex
- W4393392255
- Cited by
- 13
- References
- 42
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 6
- FWCI
- 1.77
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Briefings in Bioinformatics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (32270690, 32070671, 82102186, 32200533)
- Blue and Green Project
- Science and Technology Innovation Team of Jiangsu Province
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- prostate cancer, disease ontology, ontology construction, knowledge integration, genotype data, phenotypic data, lifestyle data, knowledge graphs, data standardization, semantic knowledge representation, precision medicine, diagnosis and treatment
- MeSH terms
- Artificial Intelligence, Humans, Male, Prostatic Neoplasms, Semantics, Biological Ontologies
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