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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2005
80views more  BMCBI 2005»
15 years 6 months ago
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
Background: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently ...
Kevin Dawson, Raymond L. Rodriguez, Wasyl Malyj
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
16 years 17 days ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
BMCBI
2010
106views more  BMCBI 2010»
15 years 6 months ago
Selection of optimal reference genes for normalization in quantitative RT-PCR
Background: Normalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introdu...
Inna Chervoneva, Yanyan Li, Stephanie Schulz, Sean...
ISNN
2005
Springer
15 years 11 months ago
An Information Criterion for Informative Gene Selection
It is important in bioinformatics research and applications to select or discover informative genes of a tumor from microarray data. However, most of the existing methods are based...
Fei Ge, Jinwen Ma
BIBE
2003
IEEE
121views Bioinformatics» more  BIBE 2003»
15 years 11 months ago
Time Series Analysis of Gene Expression and Location Data
We develop a method for integrating time series expression profiles and factor-gene binding data to quantify dynamic aspects of gene regulation. We estimate latencies for transcr...
Chen-Hsiang Yeang, Tommi Jaakkola