An Ontology for Protein Data Models

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

doi:10.1109/IEMBS.2005.1615890

19976_downloaded_stream_494.pdf (214.2Kb)

Access Status

Open access

Authors

Sidhu, Amandeep

Dillon, Tharam S.

Chang, Elizabeth

Date

2005

Type

Conference Paper

Metadata

Show full item record

Citation

Sidhu, Amandeep S. and Dillon, Tharam S. and Chang, Elizabeth. 2005. An Ontology for Protein Data Models, in Zhang, Y. T. and Roux, C. and Zhuang, T. G. (ed), 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2005), 01-04 September 2005, pp. 6120-6123. Shanghai: IEEE Engineering in Medicine and Biology Society.

Source Title

Proceedings of 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Source Conference

27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2005)

DOI

10.1109/IEMBS.2005.1615890

Faculty

Curtin Business School

School of Information Systems

Remarks

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

URI

http://hdl.handle.net/20.500.11937/33490

Collection

Curtin Research Publications

Abstract

Accelerating availability of protein sequences and structures has transformed both the theory and practice of computational biology. The current systems of nomenclature for proteins remain divergent even when the experts appreciate the underlying similarities. Interoperability of protein databases is limited to lack of progress in the way the biologists describe and conceptualize the shared biological elements in protein data. The goal of the proposed protein ontology is a step forward to address these concerns by is producing a structured vocabulary that can be applied to all proteins even as the knowledge of protein roles in the cells is still accumulating and changing. A Database of 10 Major Prion Proteins available in various Protein data sources, based on the vocabulary provided by Protein Ontology is made available.