Clustering of Microarray data via clique partitioning

被引：30
|
作者：
Kochenberger, G [1 ]
Glover, F
Alidaee, B
Wang, HB
机构：
[1] Univ Colorado, Sch Business, Denver, CO 80202 USA
[2] Univ Colorado, Leeds Sch Business, Boulder, CO 80309 USA
[3] Univ Mississippi, Sch Business, University, MS 38677 USA
[4] Texas A&M Int Univ, Sch Business, Laredo, TX 78041 USA
来源：
JOURNAL OF COMBINATORIAL OPTIMIZATION | 2005年 / 10卷 / 01期
关键词：
clustering; clique partitioning; metaheuristics;
D O I：
10.1007/s10878-005-1861-1
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Microarrays are repositories of gene expression data that hold tremendous potential for new understanding, leading to advances in functional genomics and molecular biology. Cluster analysis (CA) is an early step in the exploration of such data that is useful for purposes of data reduction, exposing hidden patterns, and the generation of hypotheses regarding the relationship between genes and phenotypes. In this paper we present a new model for the clique partitioning problem and illustrate how it can be used to perform cluster analysis in this setting.
引用
收藏
页码：77 / 92
页数：16
相关论文
共 50 条
  • [31] Network clustering via clique relaxations: A community based approach
    Verma, Anurag
    Butenko, Sergiy
    GRAPH PARTITIONING AND GRAPH CLUSTERING, 2013, 588 : 129 - 139
  • [32] A clustering system for data sequence partitioning
    Wang, Yu-Jie
    EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (01) : 659 - 666
  • [33] Partitioning biological data with transitivity clustering
    Tobias Wittkop
    Dorothea Emig
    Sita Lange
    Sven Rahmann
    Mario Albrecht
    John H Morris
    Sebastian Böcker
    Jens Stoye
    Jan Baumbach
    Nature Methods, 2010, 7 : 419 - 420
  • [34] Partitioning biological data with transitivity clustering
    Wittkop, Tobias
    Emig, Dorothea
    Lange, Sita
    Rahmann, Sven
    Albrecht, Mario
    Morris, John H.
    Boecker, Sebastian
    Stoye, Jens
    Baumbach, Jan
    NATURE METHODS, 2010, 7 (06) : 419 - 420
  • [35] THE CLIQUE-PARTITIONING PROBLEM
    BHASKER, J
    SAMAD, T
    COMPUTERS & MATHEMATICS WITH APPLICATIONS, 1991, 22 (06) : 1 - 11
  • [36] Online Clique Clustering
    Chrobak, Marek
    Durr, Christoph
    Fabijan, Aleksander
    Nilsson, Bengt J.
    ALGORITHMICA, 2020, 82 (04) : 938 - 965
  • [37] Online Clique Clustering
    Marek Chrobak
    Christoph Dürr
    Aleksander Fabijan
    Bengt J. Nilsson
    Algorithmica, 2020, 82 : 938 - 965
  • [38] FACETS OF THE CLIQUE PARTITIONING POLYTOPE
    GROTSCHEL, M
    WAKABAYASHI, Y
    MATHEMATICAL PROGRAMMING, 1990, 47 (03) : 367 - 387
  • [39] Gaussian mixture clustering and imputation of microarray data
    Ouyang, M
    Welsh, WJ
    Georgopoulos, P
    BIOINFORMATICS, 2004, 20 (06) : 917 - 923
  • [40] An Information Theoretic Divergence for Microarray Data Clustering
    Vinh, Nguyen Xuan
    Phuong, Nguyen Minh
    8TH IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING, VOLS 1 AND 2, 2008, : 527 - 533
12345