Title of article :
Hybrid SPR algorithm to select predictive genes for effectual cancer classification
Author/Authors :
SUNDARAM, Aruna Dr. M.G.R Educational and Research Institute University - Department of Computer Applications, India , VENKATA, Nandakishore Lellapalli Dr. M.G.R Educational and Research Institute University - Department of Mathematics, India , PARTHASARATHY, Rajagopalan Sarukai Dr. M.G.R Educational and Research Institute University, India
Abstract :
Designing an automated system for classifying DNA microarray data is an extremely challenging problem because of its high dimension and low amount of sample data. In this paper, a hybrid statistical pattern recognition algorithm is proposed to reduce the dimensionality and select the predictive genes for the classification of cancer. Colon cancer gene expression profiles having 62 samples of 2000 genes were used for the experiment. A gene subset of 6 highly informative genes was selected by the algorithm, which provided a classification accuracy of 93.5%.
Keywords :
Cancer classification , filters , wrappers , correlation feature selection , sequential backward search , support vector machines , DNA microarray
Journal title :
Turkish Journal of Electrical Engineering and Computer Sciences
Journal title :
Turkish Journal of Electrical Engineering and Computer Sciences
