Alpha-plane based automatic general type-2 fuzzy clustering based on simulated annealing meta-heuristic algorithm for analyzing gene expression data

2015 ◽  
Vol 64 ◽  
pp. 347-359 ◽  
Author(s):  
Abolfazl Doostparast Torshizi ◽  
Mohammad Hossein Fazel Zarandi
Keyword(s):  
Gene Expression ◽  
Simulated Annealing ◽  
Gene Expression Data ◽  
Fuzzy Clustering ◽  
Heuristic Algorithm ◽  
General Type ◽  
Expression Data

scholarly journals Biclustering Gene Expression Data Using Genetic Simulated Annealing Algorithm

2019 ◽  
Vol 8 (6) ◽  
pp. 3717-3720
Keyword(s):  
Gene Expression ◽  
Simulated Annealing ◽  
Gene Expression Data ◽  
Missing Values ◽  
Simulated Annealing Algorithm ◽  
Expression Data ◽  
Genetic Simulated Annealing Algorithm ◽  
Gene Expression Matrix ◽  
The Matrix ◽  
Missing Items

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.

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