Protein Ontology Project: 2007
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Authors
Sidhu, Amandeep
Dillon, Tharam S.
Chang, Elizabeth
Date
2007Type
Conference Paper
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Show full item recordAbstract
Protein Ontology (PO) provides integration of heterogeneous protein andbiological data sources. PO converts the enormous amounts of data collected bygeneticists and molecular biologists into information that scientists, physiciansand other health care professionals and researchers can use to easily understandthe mapping of relationships inside protein molecules, interaction between twoprotein molecules and interactions between protein and other macromolecules atcellular level. This paper discusses the updates that happened to ProteinOntology Project since it was last presented at Data Mining 2006 Conference.
Citation
Sidhu, Amandeep and Dillon, Tharam and Chang, Elizabeth. 2007. : Protein Ontology Project: 2007 , Data Mining VIII: data, text and web mining and their business applications: Transactions Information and Communications Technology, pp. 163-171. The New Forest, UK: WIT Press.
Source Title
Data Mining VIII: data, text and web mining and their business applications: Transactions Information and Communications Technology
Faculty
Curtin Business School
School of Information Systems
Department
Centre for Extended Enterprises and Business Intelligence
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Chang, Elizabeth; Sidhu, Amandeep; Dillon, Tharam S. (2005)In this paper, we proposed a Protein Ontology to integrate protein data and information from various Protein Data Sources. Protein Ontology provides the technical and scientific infrastructure and knowledge to allow ...
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Chang, Elizabeth; Sidhu, Amandeep; Sidhu, B.; Dillon, Tharam S. (2005)The rapid generation of accessible protein data sources has generated confusion over protein data representation. The protein ontology project seeks to provide a set of structured vocabularies for protein domains that can ...
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Chang, Elizabeth; Sidhu, Amandeep; Dillon, Tharam S.; Sidhu, B. (2005)These Huge amounts of Protein Structure Data make it difficult to create explanatory and predictive models that are consistent with huge volume of data. Difficulty increase when large variety of heterogeneous approaches ...