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124
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CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
15 years 7 months ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...
94
Voted
ICIP
2000
IEEE
16 years 4 months ago
Clustered Component Analysis for FMRI Signal Estimation and Classification
In this paper, we introduce a method for estimating the statistically distinct neural responses in an sequence of functional magnetic resonance images (fMRI). The crux of our meth...
Charles A. Bouman, Sea Chen, Mark J. Lowe
105
Voted
BMCBI
2007
103views more  BMCBI 2007»
15 years 2 months ago
A comprehensive evaluation of SAM, the SAM R-package and a simple modification to improve its performance
Background: The Significance Analysis of Microarrays (SAM) is a popular method for detecting significantly expressed genes and controlling the false discovery rate (FDR). Recently...
Shunpu Zhang
111
Voted
WCNC
2008
IEEE
15 years 9 months ago
Analysis of Interference from Large Clusters as Modeled by the Sum of Many Correlated Lognormals
Abstract—We examine the statistical distribution of the interference produced by a cluster of very many co-channel interferers, e.g., a sensor network, or a city full of active w...
Sebastian S. Szyszkowicz, Halim Yanikomeroglu
191
Voted
SIGMOD
1999
ACM
183views Database» more  SIGMOD 1999»
15 years 6 months ago
OPTICS: Ordering Points To Identify the Clustering Structure
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysi...
Mihael Ankerst, Markus M. Breunig, Hans-Peter Krie...