Unification of Protein Data and Knowledge Sources

  • Amandeep S. Sidhu
  • Tharam S. Dillon
  • Elizabeth Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4251)


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.


Gene Ontology Protein Data Prion Protein Knowledge Source Semantic Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Amandeep S. Sidhu
    • 1
  • Tharam S. Dillon
    • 1
  • Elizabeth Chang
    • 2
  1. 1.Faculty of Information TechnologyUniversity of TechnologySydneyAustralia
  2. 2.School of Information SystemsCurtin University of Technical UniversityPerthAustralia

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