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BMCBI
2008
95views more  BMCBI 2008»
14 years 9 months ago
Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method
Background: Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC) analysis has been used for this purpose, but ...
Joseph W. Foley, Fumiaki Katagiri
BMCBI
2007
99views more  BMCBI 2007»
14 years 9 months ago
Stratification bias in low signal microarray studies
Background: When analysing microarray and other small sample size biological datasets, care is needed to avoid various biases. We analyse a form of bias, stratification bias, that...
Brian J. Parker, Simon Günter, Justin Bedo
BMCBI
2008
129views more  BMCBI 2008»
14 years 9 months ago
Prediction of the outcome of preoperative chemotherapy in breast cancer using DNA probes that provide information on both comple
Background: DNA microarray technology has emerged as a major tool for exploring cancer biology and solving clinical issues. Predicting a patient's response to chemotherapy is...
René Natowicz, Roberto Incitti, Euler Guima...
BMCBI
2008
115views more  BMCBI 2008»
14 years 9 months ago
Probe signal correction for differential methylation hybridization experiments
Background: Non-biological signal (or noise) has been the bane of microarray analysis. Hybridization effects related to probe-sequence composition and DNA dye-probe interactions h...
Dustin P. Potter, Pearlly Yan, Tim Hui-Ming Huang,...
CORR
2010
Springer
117views Education» more  CORR 2010»
14 years 9 months ago
Evolution with Drifting Targets
We consider the question of the stability of evolutionary algorithms to gradual changes, or drift, in the target concept. We define an algorithm to be resistant to drift if, for s...
Varun Kanade, Leslie G. Valiant, Jennifer Wortman ...