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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2010
132views more  BMCBI 2010»
14 years 11 months ago
Error margin analysis for feature gene extraction
Background: Feature gene extraction is a fundamental issue in microarray-based biomarker discovery. It is normally treated as an optimization problem of finding the best predictiv...
Chi Kin Chow, Hai Long Zhu, Jessica Lacy, Winston ...
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
BIBM
2007
IEEE
137views Bioinformatics» more  BIBM 2007»
15 years 6 months ago
A Multi-metric Similarity Based Analysis of Microarray Data
Clustering has been shown to be effective in analyzing functional relationships of genes. However, no single clustering method with single distance metric is capable of capturing ...
Fatih Altiparmak, Selnur Erdal, Ozgur Ozturk, Haka...
BMCBI
2005
110views more  BMCBI 2005»
14 years 11 months ago
Considerations when using the significance analysis of microarrays (SAM) algorithm
Background: Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments...
Ola Larsson, Claes Wahlestedt, James A. Timmons
AUSDM
2006
Springer
202views Data Mining» more  AUSDM 2006»
15 years 3 months ago
A Comparative Study of Classification Methods For Microarray Data Analysis
In response to the rapid development of DNA Microarray technology, many classification methods have been used for Microarray classification. SVMs, decision trees, Bagging, Boostin...
Hong Hu, Jiuyong Li, Ashley W. Plank, Hua Wang, Gr...