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BMCBI
2006
124views more  BMCBI 2006»
13 years 7 months ago
Network-based de-noising improves prediction from microarray data
Background: Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to the noise properties of microarrays as well as...
Tsuyoshi Kato, Yukio Murata, Koh Miura, Kiyoshi As...
CSB
2005
IEEE
151views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Lossless Compression of DNA Microarray Images
Microarray experiments are characterized by a massive amount of data, usually in the form of an image. Based on the nature of microarray images, we consider the microarray in term...
Yong Zhang, Rahul Parthe, Donald A. Adjeroh
ACIIDS
2010
IEEE
170views Database» more  ACIIDS 2010»
13 years 5 months ago
On the Effectiveness of Gene Selection for Microarray Classification Methods
Microarray data usually contains a high level of noisy gene data, the noisy gene data include incorrect, noise and irrelevant genes. Before Microarray data classification takes pla...
Zhongwei Zhang, Jiuyong Li, Hong Hu, Hong Zhou
BMCBI
2006
142views more  BMCBI 2006»
13 years 7 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins
NAR
2002
141views more  NAR 2002»
13 years 7 months ago
Co-expression pattern from DNA microarray experiments as a tool for operon prediction
The prediction of operons, the smallest unit of transcription in prokaryotes, is the first step towards reconstruction of a regulatory network at the whole genome level. Sequence ...
Chiara Sabatti, Lars Rohlin, Min-Kyu Oh, James C. ...