Articoli correlati a Visual data mining in intrinsic hierarchical complex...
Visual data mining in intrinsic hierarchical complex biodata: Novel approaches for analyzing gene expression data in biomedicine and sequence data in metagenomics - Brossura
Sinossi
Complex biological data is characterized by a high dimensionality, multi-modality, missing values and noisiness, making its analysis a challenging task. Complex data consists of primary data - the core data - produced by a modern high-throughput technology, and secondary data, a collection of all kinds of respective supplementary data and background knowledge. Furthermore, biological data often has an intrinsic hierarchical structure, e.g. species in the Tree of Life. In this book, novel visual data mining approaches for the analysis of gene expression data in biomedicine and for sequence data in metagenomics are presented. To support the analysis of gene expression data, a Tree Index is developed for external validation of hierarchical clustering results and for correlation analysis between clustered primary data and external labels. To support visual inspection of the data, the REEFSOM – a metaphoric data display - is adapted to integrate clustered gene expression data, clinical data and categorical data in one display. In the domain of metagenomics, a Self-Organizing Map classifier is developed in hyperbolic space to classify small variable-length DNA fragments.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
Christian Wolfgang Martin studied computer science at theUniversities of Bielefeld and Geneva and graduated in 2003. Hereceived a scholarship of the International Graduate SchoolBioinformatics and Genome Research and obtained a Ph.D. inbioinformatics in 2009. His main interests are focused on machinelearning methods applied in biomedicine.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Compra nuovo
Visualizza questo articolo
EUR 69,90
EUR 11,00 per la spedizione da Germania a Italia
Destinazione, tempi e costiRisultati della ricerca per Visual data mining in intrinsic hierarchical complex...
Immagini fornite dal venditore
Visual data mining in intrinsic hierarchical complex biodata
Editore:
Südwestdeutscher Verlag Für Hochschulschriften Aug 2009, 2009
ISBN 10: 3838109791
ISBN 13: 9783838109794
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Complex biological data is characterized by a high dimensionality, multi-modality, missing values and noisiness, making its analysis a challenging task. Complex data consists of primary data - the core data - produced by a modern high-throughput technology, and secondary data, a collection of all kinds of respective supplementary data and background knowledge. Furthermore, biological data often has an intrinsic hierarchical structure, e.g. species in the Tree of Life. In this book, novel visual data mining approaches for the analysis of gene expression data in biomedicine and for sequence data in metagenomics are presented. To support the analysis of gene expression data, a Tree Index is developed for external validation of hierarchical clustering results and for correlation analysis between clustered primary data and external labels. To support visual inspection of the data, the REEFSOM - a metaphoric data display - is adapted to integrate clustered gene expression data, clinical data and categorical data in one display. In the domain of metagenomics, a Self-Organizing Map classifier is developed in hyperbolic space to classify small variable-length DNA fragments. 156 pp. Deutsch. Codice articolo 9783838109794
Quantità: 2 disponibili
Immagini fornite dal venditore
Visual data mining in intrinsic hierarchical complex biodata : Novel approaches for analyzing gene expression data in biomedicine and sequence data in metagenomics
Editore:
Südwestdeutscher Verlag Für Hochschulschriften, 2009
ISBN 10: 3838109791
ISBN 13: 9783838109794
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Complex biological data is characterized by a high dimensionality, multi-modality, missing values and noisiness, making its analysis a challenging task. Complex data consists of primary data - the core data - produced by a modern high-throughput technology, and secondary data, a collection of all kinds of respective supplementary data and background knowledge. Furthermore, biological data often has an intrinsic hierarchical structure, e.g. species in the Tree of Life. In this book, novel visual data mining approaches for the analysis of gene expression data in biomedicine and for sequence data in metagenomics are presented. To support the analysis of gene expression data, a Tree Index is developed for external validation of hierarchical clustering results and for correlation analysis between clustered primary data and external labels. To support visual inspection of the data, the REEFSOM - a metaphoric data display - is adapted to integrate clustered gene expression data, clinical data and categorical data in one display. In the domain of metagenomics, a Self-Organizing Map classifier is developed in hyperbolic space to classify small variable-length DNA fragments. Codice articolo 9783838109794
Quantità: 1 disponibili
Immagini fornite dal venditore
Visual data mining in intrinsic hierarchical complex biodata
Editore:
Südwestdeutscher Verlag Für Hochschulschriften Aug 2009, 2009
ISBN 10: 3838109791
ISBN 13: 9783838109794
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Neuware -Complex biological data is characterized by a high dimensionality, multi-modality, missing values and noisiness, making its analysis a challenging task. Complex data consists of primary data - the core data - produced by a modern high-throughput technology, and secondary data, a collection of all kinds of respective supplementary data and background knowledge. Furthermore, biological data often has an intrinsic hierarchical structure, e.g. species in the Tree of Life. In this book, novel visual data mining approaches for the analysis of gene expression data in biomedicine and for sequence data in metagenomics are presented. To support the analysis of gene expression data, a Tree Index is developed for external validation of hierarchical clustering results and for correlation analysis between clustered primary data and external labels. To support visual inspection of the data, the REEFSOM ¿ a metaphoric data display - is adapted to integrate clustered gene expression data, clinical data and categorical data in one display. In the domain of metagenomics, a Self-Organizing Map classifier is developed in hyperbolic space to classify small variable-length DNA fragments.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Deutsch. Codice articolo 9783838109794
Quantità: 2 disponibili
Immagini fornite dal venditore
Visual data mining in intrinsic hierarchical complex biodata | Novel approaches for analyzing gene expression data in biomedicine and sequence data in metagenomics
Editore:
Südwestdeutscher Verlag für Hochschulschriften, 2009
ISBN 10: 3838109791
ISBN 13: 9783838109794
Nuovo
Taschenbuch
Da: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Visual data mining in intrinsic hierarchical complex biodata | Novel approaches for analyzing gene expression data in biomedicine and sequence data in metagenomics | Christian W. Martin | Taschenbuch | Paperback | 156 S. | Deutsch | 2009 | Südwestdeutscher Verlag für Hochschulschriften | EAN 9783838109794 | Verantwortliche Person für die EU: Südwestdt. Verl. f. Hochschulschrift., Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Codice articolo 101491412
Quantità: 5 disponibili