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» Microarray Gene Expression Data Analysis
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BMCBI
2005
80views more  BMCBI 2005»
15 years 2 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
126
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BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
15 years 8 months 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...
110
Voted
ISNN
2005
Springer
15 years 8 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
109
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BIBE
2003
IEEE
121views Bioinformatics» more  BIBE 2003»
15 years 7 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
BMEI
2008
IEEE
15 years 4 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...