NDLI: Improved T-Cluster based scheme for combination gene scale expression data

Content Provider	IEEE Xplore Digital Library
Author	Vengatesan, K. Selvarajan, S.
Copyright Year	2012
Description	Author affiliation: Muthayammal Technical Campus, Rasipuram, Namakkal, Tamilnadu, India (Selvarajan, S.) \|\| Department of Computer Science and Engineering, Muthayammal Engineering College, Rasipuram, Namakkal, Tamilnadu, India (Vengatesan, K.)
Abstract	Clustering is an unsupervised learning technique in that there is no explicit demarcation of data as training and test data. Clustering aims to group related records by measuring similarities among the attribute. Major phase of clustering techniques is similarity measurement and it is based on different factors and parameters. The improved Nonnegative Matrix Factorization (NMF) based TCLUST (T-Clustering) algorithm is EM principle (Expectation Maximization) based algorithm, intended to search for approximate solutions. The EM algorithm is the efficient method of obtaining a solution to the mixture likelihood problem. Genes with a common function are often hypothesized to have correlated expression levels across different conditions. NMF clustering is introduced to find a small number of Meta genes, each defined as a positive linear combination of the genes in the expression data. The proposed clustering algorithm is applied to a genome scale gene expression dataset to enrichment analysis and to discover highly significant biological clusters.
Starting Page	131
Ending Page	136
File Size	476673
Page Count	6
File Format	PDF
ISBN	9781467327565
e-ISBN	9781467327589
DOI	10.1109/ICRCC.2012.6450562
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-21
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Correlation coefficient EM Algorithms TCLUST Translation Clustering algorithms Non Negative Matrix Factorization Euclidean distance Vectors Gene expression Tanimoto Correlation Coefficient
Content Type	Text
Resource Type	Article

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