A COMPARATIVE STUDY OF NEURAL NETWORK ARCHITECTURES FOR PREDICTING GENE EXPRESSION IN M. TUBERCULOSIS

Authors

  • VENKATESAN P Scientist E and Deputy Director, Department of Statististics, National Institute for Research in Tuberculosis-ICMR, Chennai,India.
  • TINTU THOMAS Department of Community Medicine, C.U.Shah Medical College, Gujarat,India.

Keywords:

microarray, artificial neural network, multilayer perceptron, radial basis function

Abstract

Identification and classification of differentially expressed genes is a challenging process.The study was performed to find applicability of supervised feed forward neural networks to solve classification problems in microarray data.We used two neural network learning algorithms namely RBF and MLP for the classification of gene expression of mycobacterium tuberculosis.The result showed that MLP and RBF classifier have similar performance and both have given high prediction.

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Published

31.03.2013

How to Cite

VENKATESAN P, & TINTU THOMAS. (2013). A COMPARATIVE STUDY OF NEURAL NETWORK ARCHITECTURES FOR PREDICTING GENE EXPRESSION IN M. TUBERCULOSIS. International Journal of Pharma and Bio Sciences, 4(1), 965–972. Retrieved from https://ijpbs.net/index.php/journal/article/view/2114

Issue

Volume 4, Issue 1, 2013

Section

Research Articles

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