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Towards Biological Sequence Data Service with Insights

Conference Paper


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Abstract


  • Testable prediction outcomes generated by computational models based on available databases are the primary sources helping to design biological experiments. Although numerous databases have been designed by collecting data either only from literature manually or together with prediction outcomes from computational models, there is currently not a comprehensive data service framework delivering better insights for these results. In this paper, we introduce a biological sequence data service towards delivering deeper insights and helping better biological experiments design. The service includes following major components: a comprehensive database for storing biological data, data analytics tools for analysing biological data, and computational models for delivering testable prediction outcomes. Specifically, we present this service in a framework for studies on host-pathogen interactions. The design of this framework aims to improve the understanding of host-pathogen interactions. The relationships of hierarchical databases and their working mechanism, specifically between PPIs and DDIs, are also presented in this framework. Finally, the preliminary and practical experiences of building computational model for prediction is discussed.

Authors


  •   Chen, Huaming (external author)
  •   Shen, Jun
  •   Wang, Lei
  •   Chi, Chi-Hung (external author)

Publication Date


  • 2018

Citation


  • Chen, H., Shen, J., Wang, L. & Chi, C. (2018). Towards Biological Sequence Data Service with Insights. IEEE Conference on Big Data (pp. 2846-2853). United States: IEEE.

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=3156&context=eispapers1

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/2150

Start Page


  • 2846

End Page


  • 2853

Place Of Publication


  • United States

Abstract


  • Testable prediction outcomes generated by computational models based on available databases are the primary sources helping to design biological experiments. Although numerous databases have been designed by collecting data either only from literature manually or together with prediction outcomes from computational models, there is currently not a comprehensive data service framework delivering better insights for these results. In this paper, we introduce a biological sequence data service towards delivering deeper insights and helping better biological experiments design. The service includes following major components: a comprehensive database for storing biological data, data analytics tools for analysing biological data, and computational models for delivering testable prediction outcomes. Specifically, we present this service in a framework for studies on host-pathogen interactions. The design of this framework aims to improve the understanding of host-pathogen interactions. The relationships of hierarchical databases and their working mechanism, specifically between PPIs and DDIs, are also presented in this framework. Finally, the preliminary and practical experiences of building computational model for prediction is discussed.

Authors


  •   Chen, Huaming (external author)
  •   Shen, Jun
  •   Wang, Lei
  •   Chi, Chi-Hung (external author)

Publication Date


  • 2018

Citation


  • Chen, H., Shen, J., Wang, L. & Chi, C. (2018). Towards Biological Sequence Data Service with Insights. IEEE Conference on Big Data (pp. 2846-2853). United States: IEEE.

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=3156&context=eispapers1

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/2150

Start Page


  • 2846

End Page


  • 2853

Place Of Publication


  • United States