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Data Integration Through Protein Ontology

Data Integration Through Protein Ontology

Amandeep S. Sidhu, Tharam S. Dillon, Elizabeth Chang
Copyright: © 2008 |Pages: 17
ISBN13: 9781599046181|ISBN10: 1599046180|ISBN13 Softcover: 9781616926571|EISBN13: 9781599046204
DOI: 10.4018/978-1-59904-618-1.ch006
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MLA

Sidhu, Amandeep S., et al. "Data Integration Through Protein Ontology." Data Mining with Ontologies: Implementations, Findings, and Frameworks, edited by Hector Oscar Nigro, et al., IGI Global, 2008, pp. 106-122. https://doi.org/10.4018/978-1-59904-618-1.ch006

APA

Sidhu, A. S., Dillon, T. S., & Chang, E. (2008). Data Integration Through Protein Ontology. In H. Nigro, S. Gonzalez Cisaro, & D. Xodo (Eds.), Data Mining with Ontologies: Implementations, Findings, and Frameworks (pp. 106-122). IGI Global. https://doi.org/10.4018/978-1-59904-618-1.ch006

Chicago

Sidhu, Amandeep S., Tharam S. Dillon, and Elizabeth Chang. "Data Integration Through Protein Ontology." In Data Mining with Ontologies: Implementations, Findings, and Frameworks, edited by Hector Oscar Nigro, Sandra Elizabeth Gonzalez Cisaro, and Daniel Hugo Xodo, 106-122. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-618-1.ch006

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Abstract

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, or structural similarity, or functional identification. Some proteins have high degree of sequence identity, or structural similarity, or similarity in functions that are unique to members of that family alone. Consequently, this approach can’t 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.

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