Extracting meaningful information from gene expression data poses a great challenge to the community of researchers in the field of computation as well as to biologists. It is possible to determine the behavioral patterns of genes such as nature of their interaction, similarity of their behavior and so on, through the analysis of gene expression data.In order to identify various patterns from gene expression data, data mining techniques are essential. Major data mining techniques which can be applied for the analysis of gene expression data include clustering, classification, association rule mining etc. Clustering is an important data mining technique for the analysis of gene expression data. However clustering has some disadvantages. To overcome the problems associated with clustering, biclustering is introduced.
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Balamurugan R received the B.E. and M.E. degree in Computer Science and Engineering in 2010 and 2012 from Anna University. He has completed his Ph.D in Information and Communication Engineering in JAN-2016 from Anna University. His areas of interest include data mining and meta-heuristic optimization techniques.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Extracting meaningful information from gene expression data poses a great challenge to the community of researchers in the field of computation as well as to biologists. It is possible to determine the behavioral patterns of genes such as nature of their interaction, similarity of their behavior and so on, through the analysis of gene expression data.In order to identify various patterns from gene expression data, data mining techniques are essential. Major data mining techniques which can be applied for the analysis of gene expression data include clustering, classification, association rule mining etc. Clustering is an important data mining technique for the analysis of gene expression data. However clustering has some disadvantages. To overcome the problems associated with clustering, biclustering is introduced. 56 pp. Englisch. Bestandsnummer des Verkäufers 9783659746390
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rengeswaran BalamuruganR. Balamurugan is currently working as a Senior Research Fellow for the DBT sponsored project at Bannari Amman Institute of Technology, Erode, Tamil Nadu, India. He received his M.E.and B.E. (Computer Science a. Bestandsnummer des Verkäufers 158429065
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Extracting meaningful information from gene expression data poses a great challenge to the community of researchers in the field of computation as well as to biologists. It is possible to determine the behavioral patterns of genes such as nature of their interaction, similarity of their behavior and so on, through the analysis of gene expression data.In order to identify various patterns from gene expression data, data mining techniques are essential. Major data mining techniques which can be applied for the analysis of gene expression data include clustering, classification, association rule mining etc. Clustering is an important data mining technique for the analysis of gene expression data. However clustering has some disadvantages. To overcome the problems associated with clustering, biclustering is introduced.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch. Bestandsnummer des Verkäufers 9783659746390
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Extracting meaningful information from gene expression data poses a great challenge to the community of researchers in the field of computation as well as to biologists. It is possible to determine the behavioral patterns of genes such as nature of their interaction, similarity of their behavior and so on, through the analysis of gene expression data.In order to identify various patterns from gene expression data, data mining techniques are essential. Major data mining techniques which can be applied for the analysis of gene expression data include clustering, classification, association rule mining etc. Clustering is an important data mining technique for the analysis of gene expression data. However clustering has some disadvantages. To overcome the problems associated with clustering, biclustering is introduced. Bestandsnummer des Verkäufers 9783659746390
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Taschenbuch. Zustand: Neu. Biclustering of Microarray Gene Expression Data : | With Heuristic Approach | Balamurugan Rengeswaran (u. a.) | Taschenbuch | 56 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659746390 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 104453567
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