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» Comparing transformation methods for DNA microarray data
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BMCBI
2004
139views more  BMCBI 2004»
14 years 11 months ago
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge r...
Jeffrey P. Townsend
SDM
2008
SIAM
157views Data Mining» more  SDM 2008»
15 years 1 months ago
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data
Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
M. Maruf Hossain, Md. Rafiul Hassan, James Bailey
CSB
2003
IEEE
153views Bioinformatics» more  CSB 2003»
15 years 5 months ago
Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks
We propose a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-...
Seiya Imoto, Tomoyuki Higuchi, Takao Goto, Kousuke...
BMCBI
2008
102views more  BMCBI 2008»
14 years 12 months ago
Significance analysis of microarray for relative quantitation of LC/MS data in proteomics
Background: Although fold change is a commonly used criterion in quantitative proteomics for differentiating regulated proteins, it does not provide an estimation of false positiv...
Bryan A. P. Roxas, Qingbo Li
BMCBI
2005
84views more  BMCBI 2005»
14 years 11 months ago
Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are e
Background: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent rep...
Leming M. Shi, Weida Tong, Hong Fang, Uwe Scherf, ...