Author : Narmadha.N 1
Date of Publication :5th February 2018
Abstract: In gene expression data analysis there are various biological data mining methods have been proposed. Among them, Co- clustering or Biclustering is a common method to extract the gene groups that behave similarly/coherently under a subset of experimental conditions. Due to increasing the dimensionality of gene expression data, the three-way clustering method called triclustering is developed recently for three-dimensional gene expression analysis. It is used to mine the coherent cluster named tricluster in three-dimensional gene expression datasets. This paper introduces a novel correlation measure to find the correlation between the genes, condition and time point in 3D gene expression dataset. The proposed method has applied to time series data obtained from yeast cell cycle analysis. From the result, it is evident that proposed algorithm mines the highly correlated 3D cluster or tricluster from gene expression data.
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