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» Microarray Gene Expression Data Analysis
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BMCBI
2006
99views more  BMCBI 2006»
15 years 2 months ago
A proposed metric for assessing the measurement quality of individual microarrays
Background: High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that...
Kyoungmi Kim, Grier P. Page, T. Mark Beasley, Step...
RECOMB
2002
Springer
16 years 2 months ago
A bayesian approach to transcript estimation from gene array data: the BEAM technique
We present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. The Bayesian Estimation of Array Measurements (BE...
Ron O. Dror, Jonathan G. Murnick, Nicola A. Rinald...
JBI
2002
126views Bioinformatics» more  JBI 2002»
15 years 2 months ago
Characteristic attributes in cancer microarrays
Rapid advances in genome sequencing and gene expression microarray technologies are providing unprecedented opportunities to identify specific genes involved in complex biological...
Indra Neil Sarkar, Paul J. Planet, T. E. Bael, S. ...
ISBRA
2007
Springer
15 years 8 months ago
Noise-Based Feature Perturbation as a Selection Method for Microarray Data
Abstract. DNA microarrays can monitor the expression levels of thousands of genes simultaneously, providing the opportunity for the identification of genes that are differentiall...
Li Chen, Dmitry B. Goldgof, Lawrence O. Hall, Stev...
BMCBI
2008
190views more  BMCBI 2008»
15 years 2 months ago
Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes
Background: Gene expression data frequently contain missing values, however, most downstream analyses for microarray experiments require complete data. In the literature many meth...
Guy N. Brock, John R. Shaffer, Richard E. Blakesle...