Application Architecture of Avian Influenza Research Collaboration Network in Korea e-Science

  • Hoon ChoiEmail author
  • JuneHawk Lee
Conference paper


In the pursuit of globalization of the AI e-Science environment, KISTI is fostering to extend the AI research community to the AI research institutes of neighboring countries and to share the AI e-Science environment with them in the near future. In this paper we introduce the application architecture of AI research collaboration network (AIRCoN). AIRCoN is a global e-Science environment for AI research conducted by KISTI. It consists of AI virus sequence information sharing system for sufficing data requirement of research community, integrated analysis environment for analyzing the mutation pattern of AI viruses and their risks, epidemic modeling and simulation environment for establishing national effective readiness strategy against AI pandemics, and knowledge portal for sharing expertise of epidemic study and unpublished research results with community members.


Avian Influenza Avian Influenza Virus Epidemic Modeling Application Architecture Protein Interaction Analysis 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1].
  2. [2].
    Melissa R. Landon,Rommie E. Amaro, Riccardo Baron, Chi Ho Ngan, David Ozonoff, J. Andrew McCammon and Sandor Vajda, Novel Druggable Hot Spots in Avian Influenza Neuraminidase H5N1 Revealed by Computational Solvent Mapping of a Reduced and Representative Receptor Ensemble, Chemical Biology & Drug Design, Vol. 71, Issue 2, pp. 106-116 (2008)CrossRefGoogle Scholar
  3. [3].
    Eichner, M, Simulation of interventions against pandemic influenza with InfluSim, Korea e-Science AHM2008, DaejeonGoogle Scholar
  4. [4].
  5. [5].
    Influenza Sequence database,
  6. [6].
  7. [7].
    Influenza sequence and epitope database,
  8. [8].
    H. Garcia-Molina, Y. Papakonstantinou , D. Quass , A. Rajaraman , Y. Sagiv ,J. Ullman, V. Vassalos ,J. Widom. The TSIMMIS approach to mediation: Data models and Languages. Journal of Intelligent Information Systems, 1997.Google Scholar
  9. [9].

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Korea Institute of Science and Technology InformationSeoulKorea

Personalised recommendations