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» Analysis of Microarray Titration Experiments
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BMCBI
2004
158views more  BMCBI 2004»
13 years 8 months ago
Incremental genetic K-means algorithm and its application in gene expression data analysis
Background: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms suc...
Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, ...
BMCBI
2006
118views more  BMCBI 2006»
13 years 8 months ago
Identification of gene expression patterns using planned linear contrasts
Background: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With ...
Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Ge...
BIOINFORMATICS
2006
96views more  BIOINFORMATICS 2006»
13 years 8 months ago
Joint estimation of calibration and expression for high-density oligonucleotide arrays
Motivation: The need for normalization in microarray experiments has been well documented in the literature. Currently, most analysis methods treat normalization and analysis as a...
Ann L. Oberg, Douglas W. Mahoney, Karla V. Ballman...
BMCBI
2011
13 years 2 days ago
Proportion statistics to detect differentially expressed genes: a comparison with log-ratio statistics
Background: In genetic transcription research, gene expression is typically reported in a test sample relative to a reference sample. Laboratory assays that measure gene expressio...
Tracy L. Bergemann, Jason Wilson
BMCBI
2002
195views more  BMCBI 2002»
13 years 8 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...