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» Combining microarrays and genetic analysis
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CSB
2005
IEEE
165views Bioinformatics» more  CSB 2005»
13 years 11 months ago
Sequential Diagonal Linear Discriminant Analysis (SeqDLDA) for Microarray Classification and Gene Identification
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
Roger Pique-Regi, Antonio Ortega, Shahab Asgharzad...
IJON
2006
95views more  IJON 2006»
13 years 9 months ago
Ensemble classifiers based on correlation analysis for DNA microarray classification
Since accurate classification of DNA microarray is a very important issue for the treatment of cancer, it is more desirable to make a decision by combining the results of various ...
Kyung-Joong Kim, Sung-Bae Cho
BMCBI
2010
125views more  BMCBI 2010»
13 years 10 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
BMCBI
2007
112views more  BMCBI 2007»
13 years 10 months ago
Selecting dissimilar genes for multi-class classification, an application in cancer subtyping
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...
BMCBI
2005
94views more  BMCBI 2005»
13 years 9 months ago
Visualization-based discovery and analysis of genomic aberrations in microarray data
Background: Chromosomal copy number changes (aneuploidies) play a key role in cancer progression and molecular evolution. These copy number changes can be studied using microarray...
Chad L. Myers, Xing Chen, Olga G. Troyanskaya