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164views more  BMCBI 2010»
9 years 10 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
198views Data Mining» more  ICDM 2010»
9 years 11 months ago
Hierarchical Ensemble Clustering
Ensemble clustering has emerged as an important elaboration of the classical clustering problems. Ensemble clustering refers to the situation in which a number of different (input)...
Li Zheng, Tao Li, Chris H. Q. Ding
168views more  TKDE 2002»
10 years 28 days ago
CLARANS: A Method for Clustering Objects for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. To this end, this paper has three main contrib...
Raymond T. Ng, Jiawei Han
142views more  PRL 1998»
10 years 29 days ago
A monothetic clustering method
: The proposed divisive clustering method performs simultaneously a hierarchy of a set of objects and a monothetic characterization of each cluster of the hierarchy. A division is ...
Marie Chavent
190views more  BIOINFORMATICS 2007»
10 years 1 months ago
Towards clustering of incomplete microarray data without the use of imputation
Motivation: Clustering technique is used to find groups of genes that show similar expression patterns under multiple experimental conditions. Nonetheless, the results obtained by...
Dae-Won Kim, Ki Young Lee, Kwang H. Lee, Doheon Le...
119views more  PR 2006»
10 years 1 months ago
Fuzzy Bayesian validation for cluster analysis of yeast cell-cycle data
Clustering for the analysis of the genes organizes the patterns into groups by the similarity of the dataset and has been used for identifying the functions of the genes in the cl...
Sung-Bae Cho, Si-Ho Yoo
169views more  PR 2008»
10 years 1 months ago
A survey of kernel and spectral methods for clustering
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
Maurizio Filippone, Francesco Camastra, Francesco ...
128views more  CSDA 2008»
10 years 1 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
134views more  BMCBI 2008»
10 years 1 months ago
Clustering cancer gene expression data: a comparative study
Background The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have propose...
Marcílio Carlos Pereira de Souto, Ivan G. C...
153views more  BMCBI 2010»
10 years 1 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...