Hierarchical information clustering by means of topologically embedded graphs

PLoS ONE

Volumn 7, Issue 3, 2012, Pages

  Song, Won Min ^a   Di Matteo, T ^a,b   Aste, Tomaso ^a,c  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^b KING'S COLLEGE LONDON   (United Kingdom)

^c UNIVERSITY OF KENT   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; CLUSTER ANALYSIS; CONTROLLED STUDY; CORRELATION COEFFICIENT; DATA PROCESSING; DBHT TECHNIQUE; GENE CLUSTER; GENE EXPRESSION PROFILING; GENE EXPRESSION SYSTEM; HIERARCHICAL INFORMATION CLUSTERING; HUMAN; HUMAN CELL; INFORMATION PROCESSING; LYMPHOMA; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; PLANAR MAXIMALLY FILTERED GRAPH; RECEIVER OPERATING CHARACTERISTIC; RELIABILITY; STATISTICAL DISTRIBUTION; GENE REGULATORY NETWORK; GENETICS; INFORMATION SCIENCE; INFORMATION SERVICE; METHODOLOGY; THEORETICAL MODEL;

CLUSTER ANALYSIS; GENE REGULATORY NETWORKS; HUMANS; INFORMATION SCIENCE; INFORMATION SERVICES; LYMPHOMA; MODELS, THEORETICAL;

EID: 84857926056     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0031929     Document Type: Article

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