Search For:

Displaying 1-4 out of 4 total
Using the Maximum Between-Class Variance for Automatic Gridding of cDNA Microarray Images
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Gui-Fang Shao, Fan Yang, Qian Zhang, Qi-Feng Zhou, Lin-Kai Luo
Issue Date:January 2013
pp. 181-192
Gridding is the first and most important step to separate the spots into distinct areas in microarray image analysis. Human intervention is necessary for most gridding methods, even if some so-called fully automatic approaches also need preset parameters. ...
 
Improving the Computational Efficiency of Recursive Cluster Elimination for Gene Selection
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Lin-Kai Luo, Deng-Feng Huang, Ling-Jun Ye, Qi-Feng Zhou, Gui-Fang Shao, Hong Peng
Issue Date:January 2011
pp. 122-129
The gene expression data are usually provided with a large number of genes and a relatively small number of samples, which brings a lot of new challenges. Selecting those informative genes becomes the main issue in microarray data analysis. Recursive clust...
 
Using the Maximum Between-Class Variance for Automatic Gridding of cDNA Microarray Images
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Fan Yang, Gui-Fang Shao, Lin-Kai Luo, Qi-Feng Zhou, Qian Zhang
Issue Date:January 2013
pp. 181-192
Gridding is the first and most important step to separate the spots into distinct areas in microarray image analysis. Human intervention is necessary for most gridding methods, even if some so-called fully automatic approaches also need preset parameters. ...
     
Improving the Computational Efficiency of Recursive Cluster Elimination for Gene Selection
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Deng-Feng Huang, Gui-Fang Shao, Hong Peng, Lin-Kai Luo, Ling-Jun Ye, Qi-Feng Zhou
Issue Date:January 2011
pp. 122-129
The gene expression data are usually provided with a large number of genes and a relatively small number of samples, which brings a lot of new challenges. Selecting those informative genes becomes the main issue in microarray data analysis. Recursive clust...
     
 1