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» Spotting effect in microarray experiments
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BMCBI
2004
128views more  BMCBI 2004»
13 years 7 months ago
Comparing transformation methods for DNA microarray data
Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed ...
Helene H. Thygesen, Aeilko H. Zwinderman
CIBCB
2006
IEEE
13 years 11 months ago
Efficient Probe Selection in Microarray Design
Abstract-- The DNA microarray technology, originally developed to measure the level of gene expression, had become one of the most widely used tools in genomic study. Microarrays h...
Leszek Gasieniec, Cindy Y. Li, Paul Sant, Prudence...
BMCBI
2006
165views more  BMCBI 2006»
13 years 7 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin
BMCBI
2007
115views more  BMCBI 2007»
13 years 7 months ago
SpliceMiner: a high-throughput database implementation of the NCBI Evidence Viewer for microarray splice variant analysis
Background: There are many fewer genes in the human genome than there are expressed transcripts. Alternative splicing is the reason. Alternatively spliced transcripts are often sp...
Ari B. Kahn, Michael C. Ryan, Hongfang Liu, Barry ...
AINA
2008
IEEE
14 years 2 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh