Wan, Cen and Barton, Carl (2024) A novel hierarchy-based knowledge discovery framework for elucidating human aging-related phenotypic abnormalities. In: SAC '24 - 39th ACM/SIGAPP Symposium on Applied Computing, 08-12 Apr 2024, Avila, Spain.
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Abstract
Aging is a complex biological process involving multiple genes that are also related to phenotypic abnormalities. However, the micro view of the associations between aging and human phenotypic abnormalities is still under-studied. We propose a novel framework, HFSKDD, that uses a new hierarchical ontology terms selection method, EL-HIP$_+$, to discover patterns between Gene Ontology and Human Phenotype Ontology databases. The experimental results confirm that EL-HIP$_+$ obtained better performance than the state-of-the-art hierarchical ontology terms selection method in predicting human phenotypic abnormality annotations, whilst HFSKDD also successfully highlighted some insightful associations between aging processes and human phenotypic abnormalities.
Metadata
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | Carl Barton |
| Date Deposited: | 26 Mar 2025 13:07 |
| Last Modified: | 10 Apr 2025 21:58 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/53243 |
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