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BMCBI
2008
157views more  BMCBI 2008»
13 years 5 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...
BMEI
2008
IEEE
13 years 6 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
BMCBI
2008
160views more  BMCBI 2008»
13 years 5 months ago
A method for analyzing censored survival phenotype with gene expression data
Background: Survival time is an important clinical trait for many disease studies. Previous works have shown certain relationship between patients' gene expression profiles a...
Tongtong Wu, Wei Sun, Shinsheng Yuan, Chun-Houh Ch...
WCE
2007
13 years 6 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
IEEEMM
2007
146views more  IEEEMM 2007»
13 years 4 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...