Two-way combinatorial clustering network

Author

Cao, Shengyu ; Liu, Laifu

Author_Institution

Dept. of Int. Econ., China Foreign Affaires Univ., Beijing, China

Volume

3

fYear

2010

fDate

21-24 May 2010

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Future Computer and Communication (ICFCC), 2010 2nd International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-5821-9

Type

conf

DOI

10.1109/ICFCC.2010.5497692

Filename

5497692