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» Analysis of Variance for Gene Expression Microarray Data
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JBI
2007
138views Bioinformatics» more  JBI 2007»
14 years 11 months ago
Towards knowledge-based gene expression data mining
ct 10 The field of gene expression data analysis has grown in the past few years from being purely data-centric to integrative, aiming at 11 complementing microarray analysis with...
Riccardo Bellazzi, Blaz Zupan
BMCBI
2006
173views more  BMCBI 2006»
14 years 12 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
BMCBI
2007
126views more  BMCBI 2007»
15 years 10 hour ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
CSDA
2008
128views more  CSDA 2008»
14 years 12 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...
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
16 years 9 days ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu