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ICASSP
2009
IEEE
14 years 2 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
APBC
2003
13 years 8 months ago
Microarray Image Processing Based on Clustering and Morphological Analysis
Microarrays allow the monitoring of expressions for tens of thousands of genes simultaneously. Image analysis is an important aspect for microarray experiments that can affect sub...
Shuanhu Wu, Hong Yan
BMCBI
2005
103views more  BMCBI 2005»
13 years 7 months ago
Quadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experiments
Background: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage o...
Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V...
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
Testing for mean and correlation changes in microarray experiments: an application for pathway analysis
Background: Microarray experiments examine the change in transcript levels of tens of thousands of genes simultaneously. To derive meaningful data, biologists investigate the resp...
Mayer Alvo, Zhongzhu Liu, Andrew Williams, Carole ...
CIBCB
2006
IEEE
14 years 1 months ago
A Model-Free Greedy Gene Selection for Microarray Sample Class Prediction
— Microarray data analysis is notoriously challenging as it involves a huge number of genes compared to only a limited number of samples. Gene selection, to detect the most signi...
Yi Shi, Zhipeng Cai, Lizhe Xu, Wei Ren, Randy Goeb...