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  • Poster presentation
  • Open Access

High content cellular microarray for automated drug target deconvolution

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BMC Proceedings20115 (Suppl 1) :P76

  • Published:


  • Public Health
  • Drug Target
  • Automate Identification
  • Statistical Robustness
  • Efficient Computational Method

Despite the promising paradigm offered by high-content screening, the concrete execution of hundred of thousands of visual cell-based experiments has remained highly challenging in terms of both statistical robustness and speed. An efficient computational method for cellular microarrays was developed at Institut Pasteur-Korea that allow for high speed, high content genome-wide siRNA screening. Details of the method and examples of data from genome-wide analyses will be featured in this presentation. In particular, we will demonstrate that the sudden ability to dramatically increase the number of experiments has created the opportunity for automated identification of a drug’s target.

Authors’ Affiliations

Discovery Biology Group, Institut Pasteur Korea, Seongnam-si, 463-400, Korea
Image Mining Group, Institut Pasteur Korea, Seongnam-si, 463-400, Korea


© Kwon et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.