Hybrid SPR algorithm to select predictive genes for effectual cancer classification

Authors

ARUNA SUNDARAM
NANDAKISHORE LELLAPALLI VENKATA
RAJAGOPALAN SARUKAI PARTHASARATHY

DOI

10.3906/elk-1203-138

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

First Page

2357

Last Page

2366

Recommended Citation

SUNDARAM, ARUNA; VENKATA, NANDAKISHORE LELLAPALLI; and PARTHASARATHY, RAJAGOPALAN SARUKAI (2013) "Hybrid SPR algorithm to select predictive genes for effectual cancer classification," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 21: No. 8, Article 18. https://doi.org/10.3906/elk-1203-138
Available at: https://journals.tubitak.gov.tr/elektrik/vol21/iss8/18