(C) 2002, SNU Biointelligence Lab, Immunocomputing for Bioarrays Alexander O. Tarakanov, et al. Proceedings of ICARIS 2002, 32-40.

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Presentation transcript:

(C) 2002, SNU Biointelligence Lab, Immunocomputing for Bioarrays Alexander O. Tarakanov, et al. Proceedings of ICARIS 2002, MEC Seminar Su Dong Kim

(C) 2002, SNU Biointelligence Lab, Introduction Biosensor : antibodies, enzymes, etc. Biochips vs. Computer microchips  Miniaturization  Integration  Parallel processing Proteomics technologies  2-D polyacrylamide gel electrophoresis with mass spectrometry  Surface-enhanced laser desorption and ionization Immune diagnostic arrays : IgG with pG Immunocomputing approach : Pattern Recognition

(C) 2002, SNU Biointelligence Lab, Bioarrays General Approach  pG-IgG pG binds to Fc-fragment of IgG  pG-HRP HRP: horseradish peroxidase  pG-CP CP : carbon particles Materials and Methods  Nitrocellulose membranes  Human IgG (Fractions II, III)  Recombinant pG Preparation of Bioarrays  Spot : 5 μl solution of IgG  Solid-phase immunoassay  Experimental results (see left)

(C) 2002, SNU Biointelligence Lab, Software (1) : Immunochip Emulator Immunochip Emulator MS Windows 2000 MS Visual C OpenGL graphic tools

(C) 2002, SNU Biointelligence Lab, Software (2) : Mathematical Bases

(C) 2002, SNU Biointelligence Lab, Software (3) : Recognition Algorithms Processing of “Paratope”

(C) 2002, SNU Biointelligence Lab, Software (4) : Recognition Results Example of Training the Emulator Detection of All Spots by Training Example of Undetected Spots

(C) 2002, SNU Biointelligence Lab, Discussion Artificial Immune System  Direct immunoassay method  Immunocomputing method Biochip  BCS (Biochip Controlling System)  Precision motorized two coordinate stage  Auto-manual or automated dispense module  Precision optical electronic detection module Biocomputer  An immunochip-based controller  Controlling of biomolecules in the micro- wells of the biochip

(C) 2002, SNU Biointelligence Lab, Conclusion Immunocomputing approach to immunoassay-based diagnostic arrays It recognizes more than 96% spots as “non-self” codes It works almost 10 times faster than traditional “MASK” method Another immunological application had been also shown advantageous