Statistical and machine learning approaches for network analysis /

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"This book explores novel graph classes and presents novel methods to classify networks. It particularly addresses the following problems: exploration of novel graph classes and their relationships among each other; existing and classical methods to analyze networks; novel graph similarity and...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Dehmer, Matthias, 1968-
Otros Autores: Basak, Subhash C., 1945-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, N.J. : Wiley, 2012.
Colección:Wiley series in computational statistics ; 707
Temas:
Research > Statistical methods.
Machine theory.
Communication > Network analysis > Graphic methods.
Information science > Statistical methods.
Recherche > Méthodes statistiques.
Théorie des automates.
Communication > Analyse de réseau > Méthodes graphiques.
MATHEMATICS > Probability & Statistics > General.
Information science > Statistical methods
Machine theory
Research > Statistical methods
Acceso en línea:Texto completo
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Tabla de Contenidos:
  • Statistical and Machine Learning Approaches for Network Analysis; Contents; Preface; Contributors; 1 A Survey of Computational Approaches to Reconstruct and Partition Biological Networks; 1.1 INTRODUCTION; 1.2 BIOLOGICAL NETWORKS; 1.2.1 Directed Networks; 1.2.2 Undirected Networks; 1.3 GENOME-WIDE MEASUREMENTS; 1.3.1 Gene Expression Data; 1.3.2 Gene Sets; 1.4 RECONSTRUCTION OF BIOLOGICAL NETWORKS; 1.4.1 Reconstruction of Directed Networks; 1.4.1.1 Boolean Networks; 1.4.1.2 Probabilistic Boolean Networks; 1.4.1.3 Bayesian Networks; 1.4.1.4 Collaborative Graph Model; 1.4.1.5 Frequency Method.

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