Data integration through protein ontology
Traditional approaches to integrate protein data generally involved keyword searches, which immediately excludes unannotated or poorly annotated data. An alternative protein annotation approach is to rely on sequence identity, structural similarity, or functional identification. Some proteins have a...
| Main Authors: | , , |
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| Format: | Book Chapter |
| Published: |
IGI Global
2007
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| Online Access: | http://hdl.handle.net/20.500.11937/33010 |
| _version_ | 1848753826489696256 |
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| author | Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth |
| author_facet | Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth |
| author_sort | Sidhu, Amandeep |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Traditional approaches to integrate protein data generally involved keyword searches, which immediately excludes unannotated or poorly annotated data. An alternative protein annotation approach is to rely on sequence identity, structural similarity, or functional identification. Some proteins have a high degree of sequence identity, structural similarity, or similarity in functions that are unique to members of that family alone. Consequently, this approach can not be generalized to integrate the protein data. Clearly, these traditional approaches have limitations in capturing and integrating data for protein annotation. For these reasons, we have adopted an alternative method that does not rely on keywords or similarity metrics, but instead uses ontology. In this chapter we discuss conceptual framework of protein ontology that has a hierarchical classification of concepts represented as classes, from general to specific; a list of attributes related to each concept, for each class; a set of relations between classes to link concepts in ontology in more complicated ways then implied by the hierarchy, to promote reuse of concepts in the ontology; and a set of algebraic operators for querying protein ontology instances. |
| first_indexed | 2025-11-14T08:30:41Z |
| format | Book Chapter |
| id | curtin-20.500.11937-33010 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:30:41Z |
| publishDate | 2007 |
| publisher | IGI Global |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-330102017-01-30T13:34:28Z Data integration through protein ontology Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth Traditional approaches to integrate protein data generally involved keyword searches, which immediately excludes unannotated or poorly annotated data. An alternative protein annotation approach is to rely on sequence identity, structural similarity, or functional identification. Some proteins have a high degree of sequence identity, structural similarity, or similarity in functions that are unique to members of that family alone. Consequently, this approach can not be generalized to integrate the protein data. Clearly, these traditional approaches have limitations in capturing and integrating data for protein annotation. For these reasons, we have adopted an alternative method that does not rely on keywords or similarity metrics, but instead uses ontology. In this chapter we discuss conceptual framework of protein ontology that has a hierarchical classification of concepts represented as classes, from general to specific; a list of attributes related to each concept, for each class; a set of relations between classes to link concepts in ontology in more complicated ways then implied by the hierarchy, to promote reuse of concepts in the ontology; and a set of algebraic operators for querying protein ontology instances. 2007 Book Chapter http://hdl.handle.net/20.500.11937/33010 IGI Global restricted |
| spellingShingle | Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth Data integration through protein ontology |
| title | Data integration through protein ontology |
| title_full | Data integration through protein ontology |
| title_fullStr | Data integration through protein ontology |
| title_full_unstemmed | Data integration through protein ontology |
| title_short | Data integration through protein ontology |
| title_sort | data integration through protein ontology |
| url | http://hdl.handle.net/20.500.11937/33010 |