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» Improved Gene Selection for Classification of Microarrays
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BMCBI
2005
112views more  BMCBI 2005»
13 years 7 months ago
Towards precise classification of cancers based on robust gene functional expression profiles
Background: Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. Th...
Zheng Guo, Tianwen Zhang, Xia Li, Qi Wang, Jianzhe...
BMCBI
2008
157views more  BMCBI 2008»
13 years 7 months ago
Dimension reduction with redundant gene elimination for tumor classification
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
Xue-Qiang Zeng, Guo-Zheng Li, Jack Y. Yang, Mary Q...
BIBE
2007
IEEE
176views Bioinformatics» more  BIBE 2007»
14 years 1 months ago
HICCUP: Hierarchical Clustering Based Value Imputation using Heterogeneous Gene Expression Microarray Datasets
Abstract—A novel microarray value imputation method, HICCUP1 , is presented. HICCUP improves upon existing value imputation methods in the several ways. (1) By judiciously integr...
Qiankun Zhao, Prasenjit Mitra, Dongwon Lee, Jaewoo...
BMCBI
2006
153views more  BMCBI 2006»
13 years 7 months ago
Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive
Background: Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in ...
Hiro Takahashi, Takeshi Nemoto, Teruhiko Yoshida, ...
BMCBI
2007
120views more  BMCBI 2007»
13 years 7 months ago
Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures
Background: When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff be...
Xin Lu, David L. Perkins