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» Analysis of Variance for Gene Expression Microarray Data
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IV
2007
IEEE
178views Visualization» more  IV 2007»
15 years 7 months ago
Viewing the Larger Context of Genomic Data through Horizontal Integration
Genomics is an important emerging scientific field that relies on meaningful data visualization as a key step in analysis. Specifically, most investigation of gene expression micr...
Matthew A. Hibbs, Grant Wallace, Maitreya J. Dunha...
BMCBI
2006
154views more  BMCBI 2006»
15 years 1 months ago
Analysis with respect to instrumental variables for the exploration of microarray data structures
Background: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various fa...
Florent Baty, Michaël Facompré, Jan Wi...
BMCBI
2010
152views more  BMCBI 2010»
15 years 1 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...
BMCBI
2008
179views more  BMCBI 2008»
15 years 1 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao
136
Voted
BMCBI
2007
149views more  BMCBI 2007»
15 years 1 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