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» Evaluation of clustering algorithms for gene expression data
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BMCBI
2011
14 years 4 months ago
Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in i
Background: In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focuse...
Paolo G. V. Martini, Davide Risso, Gabriele Sales,...
BMCBI
2010
243views more  BMCBI 2010»
14 years 9 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
KDD
2004
ACM
145views Data Mining» more  KDD 2004»
15 years 9 months ago
Mining coherent gene clusters from gene-sample-time microarray data
Extensive studies have shown that mining microarray data sets is important in bioinformatics research and biomedical applications. In this paper, we explore a novel type of genesa...
Daxin Jiang, Jian Pei, Murali Ramanathan, Chun Tan...
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
15 years 1 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...
87
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AUSAI
2005
Springer
15 years 3 months ago
Finding Similar Patterns in Microarray Data
Abstract. In this paper we propose a clustering algorithm called sCluster for analysis of gene expression data based on pattern-similarity. The algorithm captures the tight cluster...
Xiangsheng Chen, Jiuyong Li, Grant Daggard, Xiaodi...