Improving the classification of cardinality phenotypes using collections
Abstract Motivation Phenotypes are observable characteristics of an organism and they can be highly variable. Information about phenotypes is collected in a clinical context to characterize disease, and is also collected in model organisms and stored in model organism databases where they are used t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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BMC
2023-08-01
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| Series: | Journal of Biomedical Semantics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13326-023-00290-y |
| _version_ | 1797555621901369344 |
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| author | Sarah M. Alghamdi Robert Hoehndorf |
| author_facet | Sarah M. Alghamdi Robert Hoehndorf |
| author_sort | Sarah M. Alghamdi |
| collection | DOAJ |
| description | Abstract Motivation Phenotypes are observable characteristics of an organism and they can be highly variable. Information about phenotypes is collected in a clinical context to characterize disease, and is also collected in model organisms and stored in model organism databases where they are used to understand gene functions. Phenotype data is also used in computational data analysis and machine learning methods to provide novel insights into disease mechanisms and support personalized diagnosis of disease. For mammalian organisms and in a clinical context, ontologies such as the Human Phenotype Ontology and the Mammalian Phenotype Ontology are widely used to formally and precisely describe phenotypes. We specifically analyze axioms pertaining to phenotypes of collections of entities within a body, and we find that some of the axioms in phenotype ontologies lead to inferences that may not accurately reflect the underlying biological phenomena. Results We reformulate the phenotypes of collections of entities using an ontological theory of collections. By reformulating phenotypes of collections in phenotypes ontologies, we avoid potentially incorrect inferences pertaining to the cardinality of these collections. We apply our method to two phenotype ontologies and show that the reformulation not only removes some problematic inferences but also quantitatively improves biological data analysis. |
| first_indexed | 2024-03-10T16:50:06Z |
| format | Article |
| id | doaj.art-c2f6983072124d909fac203dab9ffd52 |
| institution | Directory Open Access Journal |
| issn | 2041-1480 |
| language | English |
| last_indexed | 2024-03-10T16:50:06Z |
| publishDate | 2023-08-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Biomedical Semantics |
| spelling | doaj.art-c2f6983072124d909fac203dab9ffd522023-11-20T11:21:25ZengBMCJournal of Biomedical Semantics2041-14802023-08-0114111110.1186/s13326-023-00290-yImproving the classification of cardinality phenotypes using collectionsSarah M. Alghamdi0Robert Hoehndorf1Computational Bioscience Research Center (CBRC), Computer, Electrical, and Mathematical Sciences & Engineering Division, King Abdullah University of Science and TechnologyComputational Bioscience Research Center (CBRC), Computer, Electrical, and Mathematical Sciences & Engineering Division, King Abdullah University of Science and TechnologyAbstract Motivation Phenotypes are observable characteristics of an organism and they can be highly variable. Information about phenotypes is collected in a clinical context to characterize disease, and is also collected in model organisms and stored in model organism databases where they are used to understand gene functions. Phenotype data is also used in computational data analysis and machine learning methods to provide novel insights into disease mechanisms and support personalized diagnosis of disease. For mammalian organisms and in a clinical context, ontologies such as the Human Phenotype Ontology and the Mammalian Phenotype Ontology are widely used to formally and precisely describe phenotypes. We specifically analyze axioms pertaining to phenotypes of collections of entities within a body, and we find that some of the axioms in phenotype ontologies lead to inferences that may not accurately reflect the underlying biological phenomena. Results We reformulate the phenotypes of collections of entities using an ontological theory of collections. By reformulating phenotypes of collections in phenotypes ontologies, we avoid potentially incorrect inferences pertaining to the cardinality of these collections. We apply our method to two phenotype ontologies and show that the reformulation not only removes some problematic inferences but also quantitatively improves biological data analysis.https://doi.org/10.1186/s13326-023-00290-yCardinality phenotypesPhenotype ontologiesGenotype–phenotype associations |
| spellingShingle | Sarah M. Alghamdi Robert Hoehndorf Improving the classification of cardinality phenotypes using collections Journal of Biomedical Semantics Cardinality phenotypes Phenotype ontologies Genotype–phenotype associations |
| title | Improving the classification of cardinality phenotypes using collections |
| title_full | Improving the classification of cardinality phenotypes using collections |
| title_fullStr | Improving the classification of cardinality phenotypes using collections |
| title_full_unstemmed | Improving the classification of cardinality phenotypes using collections |
| title_short | Improving the classification of cardinality phenotypes using collections |
| title_sort | improving the classification of cardinality phenotypes using collections |
| topic | Cardinality phenotypes Phenotype ontologies Genotype–phenotype associations |
| url | https://doi.org/10.1186/s13326-023-00290-y |
| work_keys_str_mv | AT sarahmalghamdi improvingtheclassificationofcardinalityphenotypesusingcollections AT roberthoehndorf improvingtheclassificationofcardinalityphenotypesusingcollections |