Verwandte Artikel zu Clustering Algorithms for Biological Data
Inhaltsangabe
With the recent advances of data generation and acquisition systems and the success of several projects such as Human Genome, a large number of databases, especially in biological field are now available worldwide. The growing rate of such databases is also exponential. There is a need to explore and analyze such massive data to infer some inherent information. Clustering has been recognized as one of the widely used data mining techniques which is essential for data analysis to reveal natural structures and to identify interesting patterns in the underlying data. In the last decade, significant amount of research work has been carried out on cluster analysis and a large number of algorithms have been developed, particularly for biological data. Recently, much attention has been paid to develop various clustering algorithms based on neighborhood graphs such as minimum spanning tree (MST), Voronoi diagram and kd-trees. In this book, we mainly report on the hierarchical, partitional, density-based and graph-based clustering algorithms which are developed using such neighborhood graphs.
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Reseña del editor
With the recent advances of data generation and acquisition systems and the success of several projects such as Human Genome, a large number of databases, especially in biological field are now available worldwide. The growing rate of such databases is also exponential. There is a need to explore and analyze such massive data to infer some inherent information. Clustering has been recognized as one of the widely used data mining techniques which is essential for data analysis to reveal natural structures and to identify interesting patterns in the underlying data. In the last decade, significant amount of research work has been carried out on cluster analysis and a large number of algorithms have been developed, particularly for biological data. Recently, much attention has been paid to develop various clustering algorithms based on neighborhood graphs such as minimum spanning tree (MST), Voronoi diagram and kd-trees. In this book, we mainly report on the hierarchical, partitional, density-based and graph-based clustering algorithms which are developed using such neighborhood graphs.
Biografía del autor
Dr. Damodar Reddy Edla is an Asst. Professor in the department of Computer Science & Engineering, National Institute of Technology Goa, India. Dr. Prasanta K. Jana is a Professor and Head of the department of Computer Science & Engineering, Indian School of Mines, Dhanbad, India. Prof. Jana is a Senior Member of IEEE, USA (August 2009-May 2013)
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Clustering Algorithms for Biological Data
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LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659454745
ISBN 13: 9783659454745
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Edla Damodar ReddyDr. Damodar Reddy Edla is an Asst. Professor in the department of Computer Science & Engineering, National Institute of Technology Goa, India. Dr. Prasanta K. Jana is a Professor and Head of the department of Co. Bestandsnummer des Verkäufers 5157137
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Clustering Algorithms for Biological Data
Verlag:
LAP LAMBERT Academic Publishing Sep 2013, 2013
ISBN 10: 3659454745
ISBN 13: 9783659454745
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the recent advances of data generation and acquisition systems and the success of several projects such as Human Genome, a large number of databases, especially in biological field are now available worldwide. The growing rate of such databases is also exponential. There is a need to explore and analyze such massive data to infer some inherent information. Clustering has been recognized as one of the widely used data mining techniques which is essential for data analysis to reveal natural structures and to identify interesting patterns in the underlying data. In the last decade, significant amount of research work has been carried out on cluster analysis and a large number of algorithms have been developed, particularly for biological data. Recently, much attention has been paid to develop various clustering algorithms based on neighborhood graphs such as minimum spanning tree (MST), Voronoi diagram and kd-trees. In this book, we mainly report on the hierarchical, partitional, density-based and graph-based clustering algorithms which are developed using such neighborhood graphs. 148 pp. Englisch. Bestandsnummer des Verkäufers 9783659454745
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Clustering Algorithms for Biological Data
Verlag:
LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659454745
ISBN 13: 9783659454745
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the recent advances of data generation and acquisition systems and the success of several projects such as Human Genome, a large number of databases, especially in biological field are now available worldwide. The growing rate of such databases is also exponential. There is a need to explore and analyze such massive data to infer some inherent information. Clustering has been recognized as one of the widely used data mining techniques which is essential for data analysis to reveal natural structures and to identify interesting patterns in the underlying data. In the last decade, significant amount of research work has been carried out on cluster analysis and a large number of algorithms have been developed, particularly for biological data. Recently, much attention has been paid to develop various clustering algorithms based on neighborhood graphs such as minimum spanning tree (MST), Voronoi diagram and kd-trees. In this book, we mainly report on the hierarchical, partitional, density-based and graph-based clustering algorithms which are developed using such neighborhood graphs. Bestandsnummer des Verkäufers 9783659454745
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Clustering Algorithms for Biological Data
Verlag:
LAP LAMBERT Academic Publishing Sep 2013, 2013
ISBN 10: 3659454745
ISBN 13: 9783659454745
Neu
Taschenbuch
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -With the recent advances of data generation and acquisition systems and the success of several projects such as Human Genome, a large number of databases, especially in biological field are now available worldwide. The growing rate of such databases is also exponential. There is a need to explore and analyze such massive data to infer some inherent information. Clustering has been recognized as one of the widely used data mining techniques which is essential for data analysis to reveal natural structures and to identify interesting patterns in the underlying data. In the last decade, significant amount of research work has been carried out on cluster analysis and a large number of algorithms have been developed, particularly for biological data. Recently, much attention has been paid to develop various clustering algorithms based on neighborhood graphs such as minimum spanning tree (MST), Voronoi diagram and kd-trees. In this book, we mainly report on the hierarchical, partitional, density-based and graph-based clustering algorithms which are developed using such neighborhood graphs.Books on Demand GmbH, Überseering 33, 22297 Hamburg 148 pp. Englisch. Bestandsnummer des Verkäufers 9783659454745
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Clustering Algorithms For Biological Data
Verlag:
Lap Lambert Academic Publishing, 2013
ISBN 10: 3659454745
ISBN 13: 9783659454745
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Paperback. Zustand: Brand New. 148 pages. 8.66x5.91x0.34 inches. In Stock. Bestandsnummer des Verkäufers __3659454745
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Beispielbild für diese ISBN
Clustering Algorithms For Biological Data
Verlag:
Lap Lambert Academic Publishing, 2013
ISBN 10: 3659454745
ISBN 13: 9783659454745
Neu
Paperback
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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Paperback. Zustand: Brand New. 148 pages. 8.66x5.91x0.34 inches. In Stock. Bestandsnummer des Verkäufers 3659454745
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