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BMC Proceedings

Open Access

High content cellular microarray for automated drug target deconvolution

  • Yong-Jun Kwon1,
  • Hi Chul Kim1,
  • Nam Youl Kim1,
  • Seo Yeon Choi1,
  • Sungyong Jung1 and
  • Auguste Genovesio2
BMC Proceedings20115(Suppl 1):P76

Published: 10 January 2011


Public HealthDrug TargetAutomate IdentificationStatistical RobustnessEfficient 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, Korea
Image Mining Group, Institut Pasteur Korea, Seongnam-si, 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.