Title :
Two-way combinatorial clustering network
Author :
Cao, Shengyu ; Liu, Laifu
Author_Institution :
Dept. of Int. Econ., China Foreign Affaires Univ., Beijing, China
Abstract :
Two trends in clustering (also called unsupervised classification) problem: from one-way to two-way and from tree structure to net structure, are integrated in this paper to a framework of two-way combinatorial clustering network (TWCCN). The theory of directed branch-connected tree (DBCT) is constructed to describe the model of TWCCN, and algorithms based on nonnegative matrix factorization (NMF) called bootstrap NMF are proposed to build TWCCN. We show the method make sense take examples for the clustering of gene expression data and the problem of phylogenetics in bioinformatics.
Keywords :
bioinformatics; matrix decomposition; pattern clustering; trees (mathematics); NMF; TWCCN; bioinformatics; bootstrap nonnegative matrix factorization; directed branch connected tree; gene expression data; net structure; phylogenetics problem; two way combinatorial clustering network; Bioinformatics; Classification tree analysis; Clustering algorithms; Data analysis; Electronic mail; Gene expression; Mathematical model; Phylogeny; Tree data structures; Tree graphs; bioinformatics; bootstrap nonnegative matrix factorization; directed branch-connected tree; two-way combinatorial clustering network;
Conference_Titel :
Future Computer and Communication (ICFCC), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5821-9
DOI :
10.1109/ICFCC.2010.5497692
