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BIBE
2007
IEEE
127views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Gene Selection via Matrix Factorization
The recent development of microarray gene expression techniques have made it possible to offer phenotype classification of many diseases. However, in gene expression data analysis...
Fei Wang, Tao Li
WCE
2007
13 years 8 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...
BMCBI
2006
97views more  BMCBI 2006»
13 years 7 months ago
Selecting normalization genes for small diagnostic microarrays
Background: Normalization of gene expression microarrays carrying thousands of genes is based on assumptions that do not hold for diagnostic microarrays carrying only few genes. T...
Jochen Jaeger, Rainer Spang
BMCBI
2007
149views more  BMCBI 2007»
13 years 7 months ago
Robust imputation method for missing values in microarray data
Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
Dankyu Yoon, Eun-Kyung Lee, Taesung Park
JIPS
2007
134views more  JIPS 2007»
13 years 7 months ago
An Efficient Functional Analysis Method for Micro-array Data Using Gene Ontology
: Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of ...
Dong-wan Hong, Jong-keun Lee, Sung-soo Park, Sang-...