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Feature selection in hexamplot to assess drug effect in CDNA microarray experiments

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Three-color cDNA microarray experiments are designed to assess drug effects on a genomic scale in an original way. With this kind of expression data, we propose an effective algorithm, named HoughFeature, to extract the significant features of polymorphic gene expressions to quantify drug effects in hexaMplots. The Hough technique is used in our algorithm to detect the featured lines in hexaMplots corresponding to the diverse levels of drug effects on differentially expressed genes. Thus, based on hexaMplots, the side and therapeutic effects of drugs can be quantified with our methodology. We apply the framework to the experimental microarray data to assess the complex effect of PW-1 (an extract of Chinese medicine) on TCDD toxified HepG2 cells in detail. Such a methodology may be useful in forefront gene therapy to predict disease susceptibility, implement drug therapy, and assess their effects. © 2007 IEEE.
Original languageEnglish
Title of host publicationProceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007
Pages2202-2207
Volume4
DOIs
Publication statusPublished - 2007
Event6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 - Hong Kong, China
Duration: 19 Aug 200722 Aug 2007

Publication series

Name
Volume4

Conference

Conference6th International Conference on Machine Learning and Cybernetics, ICMLC 2007
PlaceChina
CityHong Kong
Period19/08/0722/08/07

Research Keywords

  • Gene expression
  • HexaMplot
  • Hough transform
  • HoughFeature
  • Three-color cDNA microarray

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