Unification of protein data and knowledge sources
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. Alt...
| Main Authors: | , , |
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| Format: | Conference Paper |
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Springer-Verlag
2006
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| Online Access: | http://hdl.handle.net/20.500.11937/25602 |
| _version_ | 1848751755070799872 |
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| author | Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth |
| author_facet | Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth |
| author_sort | Sidhu, Amandeep |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T07:57:46Z |
| format | Conference Paper |
| id | curtin-20.500.11937-25602 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:57:46Z |
| publishDate | 2006 |
| publisher | Springer-Verlag |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-256022019-02-19T05:35:34Z Unification of protein data and knowledge sources Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth Protein ontology databases scientific databases data proteomics structured vocabulary 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. 2006 Conference Paper http://hdl.handle.net/20.500.11937/25602 10.1007/11892960_88 Springer-Verlag restricted |
| spellingShingle | Protein ontology databases scientific databases data proteomics structured vocabulary Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth Unification of protein data and knowledge sources |
| title | Unification of protein data and knowledge sources |
| title_full | Unification of protein data and knowledge sources |
| title_fullStr | Unification of protein data and knowledge sources |
| title_full_unstemmed | Unification of protein data and knowledge sources |
| title_short | Unification of protein data and knowledge sources |
| title_sort | unification of protein data and knowledge sources |
| topic | Protein ontology databases scientific databases data proteomics structured vocabulary |
| url | http://hdl.handle.net/20.500.11937/25602 |