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BMCBI
2004
181views more  BMCBI 2004»
14 years 9 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
APBC
2004
164views Bioinformatics» more  APBC 2004»
14 years 11 months ago
Cluster Ensemble and Its Applications in Gene Expression Analysis
Huge amount of gene expression data have been generated as a result of the human genomic project. Clustering has been used extensively in mining these gene expression data to find...
Xiaohua Hu, Illhoi Yoo
BIBE
2007
IEEE
195views Bioinformatics» more  BIBE 2007»
15 years 4 months ago
Finding Clusters of Positive and Negative Coregulated Genes in Gene Expression Data
— In this paper, we propose a system for finding partial positive and negative coregulated gene clusters in microarray data. Genes are clustered together if they show the same p...
Kerstin Koch, Stefan Schönauer, Ivy Jansen, J...
VLDB
2004
ACM
143views Database» more  VLDB 2004»
15 years 3 months ago
GPX: Interactive Mining of Gene Expression Data
Discovering co-expressed genes and coherent expression patterns in gene expression data is an important data analysis task in bioinformatics research and biomedical applications. ...
Daxin Jiang, Jian Pei, Aidong Zhang
BMCBI
2008
114views more  BMCBI 2008»
14 years 9 months ago
Partial mixture model for tight clustering of gene expression time-course
Background: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively l...
Yinyin Yuan, Chang-Tsun Li, Roland Wilson