Artículos relacionados a Biclustering of Microarray Gene Expression Data: With...
Sinopsis
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.
"Sinopsis" puede pertenecer a otra edición de este libro.
Reseña del editor
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialLAP Lambert Academic Publishing
- Año de publicación2015
- ISBN 10 3659746398
- ISBN 13 9783659746390
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas56
- Contacto del fabricanteno disponible
Comprar nuevo
Ver este artículo
EUR 35,90
EUR 11,00 gastos de envío desde Alemania a España
Destinos, gastos y plazos de envíoResultados de la búsqueda para Biclustering of Microarray Gene Expression Data: With...
Imagen del vendedor
Biclustering of Microarray Gene Expression Data :
Publicado por
LAP Lambert Academic Publishing Jul 2015, 2015
ISBN 10: 3659746398
ISBN 13: 9783659746390
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783659746390
Cantidad disponible: 2 disponibles
Imagen del vendedor
Biclustering of Microarray Gene Expression Data : : With Heuristic Approach
Publicado por
LAP Lambert Academic Publishing, 2015
ISBN 10: 3659746398
ISBN 13: 9783659746390
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783659746390
Cantidad disponible: 1 disponibles
Imagen del vendedor
Biclustering of Microarray Gene Expression Data :
Publicado por
LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659746398
ISBN 13: 9783659746390
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: 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. Nº de ref. del artículo: 158429065
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Biclustering of Microarray Gene Expression Data :
Publicado por
LAP Lambert Academic Publishing Jul 2015, 2015
ISBN 10: 3659746398
ISBN 13: 9783659746390
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 56 pp. Englisch. Nº de ref. del artículo: 9783659746390
Cantidad disponible: 2 disponibles