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» Clustering cancer gene expression data: a comparative study
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98
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BMCBI
2007
113views more  BMCBI 2007»
14 years 11 months ago
miRAS: a data processing system for miRNA expression profiling study
Background: The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even a...
Feng Tian, Huayue Zhang, Xinyu Zhang, Chi Song, Yo...
BMCBI
2010
125views more  BMCBI 2010»
14 years 11 months ago
Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types
Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in stand...
Noor B. Dawany, Aydin Tozeren
125
Voted
CANDC
2005
ACM
14 years 11 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
97
Voted
BMCBI
2008
102views more  BMCBI 2008»
14 years 11 months ago
Response projected clustering for direct association with physiological and clinical response data
Background: Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients'...
Sung-Gon Yi, Taesung Park, Jae K. Lee
104
Voted
AUSAI
2007
Springer
15 years 3 months ago
Hybrid Methods to Select Informative Gene Sets in Microarray Data Classification
Abstract. One of the key applications of microarray studies is to select and classify gene expression profiles of cancer and normal subjects. In this study, two hybrid approaches
Pengyi Yang, Zili Zhang