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dc.contributor.authorSidhu, Amandeep
dc.contributor.authorDillon, Tharam S.
dc.contributor.authorChang, Elizabeth
dc.date.accessioned2017-01-30T12:15:34Z
dc.date.available2017-01-30T12:15:34Z
dc.date.created2008-11-12T23:32:47Z
dc.date.issued2007
dc.identifier.citationSidhu, Amandeep S and Dillon, Tharam S and Chang, Elizabeth. 2007. : Ontology algebra for composition of protein data sources, in Damiani, Ernesto (ed), 2007 IEEE International Conference on granular Computing (GcC 2007), Nov 02 2007, pp. 144-150. Silicon Valley, USA: IEEE Computer Society.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/19742
dc.identifier.doi10.1109/BIBMW.2007.4425412
dc.description.abstract

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 gathers data from multiple perspectives. In order to facilitate computational processing data, it is especially critical to develop standardized structured data representation model formats for proteomics data. In this paper we describe a Protein Ontology Model for integrating protein databases and deduce a structured vocabulary for understanding process of protein synthesis completely. Proposed Protein Ontology Model provides biologists and scientists with a description of sequence, structure and functions of protein and also provides interpretation of various factors on final protein structure conformation. The Structured Vocabulary for Protein Data, describing Protein Ontology is composed of various Type Definitions for Protein Entry Details, Sequence and Structural Information of Proteins, Structural Domain Family of Protein, Cellular Function of Protein, Chemical Bonds present in the Protein, and External Constraints deciding final protein conformation. The Proposed Ontology Model will provide easier ways to predict and understand proteins.

dc.publisherIEEE Computer Society
dc.titleOntology algebra for composition of protein data sources
dc.typeConference Paper
dcterms.source.startPage144
dcterms.source.endPage150
dcterms.source.titleProceedings of the 2007 IEEE international conference on data mining inbioinformatics (DMB 2007)
dcterms.source.seriesProceedings of the 2007 IEEE international conference on data mining inbioinformatics (DMB 2007)
dcterms.source.conference2007 IEEE International Conference on granular Computing (GcC 2007)
dcterms.source.conference-start-dateNov 02 2007
dcterms.source.conferencelocationSilicon Valley, USA
dcterms.source.placeUSA
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Copyright 2007 IEEE

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curtin.departmentCentre for Extended Enterprises and Business Intelligence
curtin.identifierEPR-2631
curtin.accessStatusOpen access


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