Biclustering Gene Expression Data Using Genetic Simulated Annealing Algorithm
M. Ramkumar1, G. Nanthakumar2
1M.Ramkumar, Research Scholar, Sri Satya Sai University of Technology & Medical Sciences, (Madhya Pradesh), India.
2Dr. G.Nanthakumar, Associate Professor, Anjalai Ammal Mahalingam Engineering College, (Tamil Nadu), India.
Manuscript received on February 01, 2019. | Revised Manuscript received on February 14, 2019. | Manuscript published on August 30, 2019. | PP: 3717-3720 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9380088619/19©BEIESP | DOI: 10.35940/ijeat.F9380.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: DNA microarray technology produces gene expression matrix that consists of an inexorably missing entries due to poor experimental procedures. The missing values are predicted in the matrix for gene expression data are considered to be essential, since most algorithms analyse the gene expression that usually needs a matrix without missing values. In order to address this issue, the present study biclustering Genetic based Simulated Annealing (Genetic SA) algorithm to predict the items that are missing in the gene expression data. The present study uses biclustering method that is considered to be essential for clustering the gene expression data. The performance evaluation shows that the proposed Genetic SA for gene data expression predicts the missing items in an accurate manner than the existing methods.
Keywords: Gene Expression Data, Biclustering Algorithm.