Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Auteur(s) : Dehmer, Matthias (1968-....)
Titre(s) : Statistical and machine learning approaches for network analysis [Texte électronique] / Matthias Dehmer, Subhash C. Basak
Publication : Hoboken, N.J. : Wiley, 2012
Description matérielle : 1 online resource
Collection : Wiley Series in Computational Statistics ; v.707
Note(s) : Includes bibliographical references and index. - Print version record and CIP data provided by publisher.
English.
"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 graph classification techniques based on machine
learning methods; and applications of graph classification and graph mining. Key topics
are addressed in depth including the mathematical definition of novel graph classes,
i.e. generalized trees and directed universal hierarchical graphs, and the application
areas in which to apply graph classes to practical problems in computational biology,
computer science, mathematics, mathematical psychology, etc"
Autre(s) auteur(s) : Basak, Subhash C. (1945-....). Fonction indéterminée
Sujet(s) : Recherche -- Méthodes statistiques
Sciences de l'information -- Méthodes statistiques
Indice(s) Dewey :
511.5 (23e éd.) = Théorie des graphes (mathématiques)
Identifiants, prix et caractéristiques : ISBN 9781118346990
Identifiant de la notice : ark:/12148/cb44653379x
Notice n° :
FRBNF44653379
(notice reprise d'un réservoir extérieur)
Table des matières : 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.
