Unification of protein data and knowledge sources

Sidhu, Amandeep; Dillon, Tharam S.; Chang, Elizabeth

doi:10.1007/11892960_88

Access Status

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Authors

Sidhu, Amandeep

Dillon, Tharam S.

Chang, Elizabeth

Date

2006

Type

Conference Paper

Metadata

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Citation

Sidhu, Amandeep and Dillon, Tharam and Chang, Elizabeth. 2006. : Unification of protein data and knowledge sources, in Gabrys, B. and Howlett, R.J. and Jain, L.C. (ed), 10th International Conference on Knowledge-based Intelligent Information and Engineering Systems (KES 2006), Oct 09 2006, pp. 728-737. Bournemouth, UK: Springer-Verlag.

Source Title

Lecture Notes in Artificial Intelligence (LNAI-4251): Knowledge-based Intelligent Information and Engineering Systems (KES 2006)

Source Conference

10th International Conference on Knowledge-based Intelligent Information and Engineering Systems (KES 2006)

DOI

10.1007/11892960_88

Faculty

Curtin Business School

School

Centre for Extended Enterprises and Business Intelligence

Remarks

The original publication is available at http://www.springerlink.com

The link to this article is:

http://dx.doi.org/10.1007/11892960_88

URI

http://hdl.handle.net/20.500.11937/25602

Collection

Curtin Research Publications

Abstract

Advances in technology and the growth of life sciences are generating ever increasing amounts of data. High-throughput techniques are regularly used to capture thousands of data points in an experiment. The results of these experiments normally end up in scientific databases and publications. Although there have been concerted efforts to capture more scientific data in specialist databases, it is generally acknowledged that only 20 per cent of biological knowledge and data is available in a structured format. The remaining 80 per cent of biological information is hidden in the unstructured scientific results and texts. Protein Ontology (PO) discussed in this paper provides a common structured vocabulary for this structured and unstructured information and provides researchers a medium to share knowledge in proteomics domain. It consists of concepts, which are data descriptors for proteomics data and the relations among these concepts. Protein Ontology provides description for protein domains that can be used to describe proteins in any organism.