Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
Background: Maximizing the utility of DNA microarray data requires optimization of data acquisition through selection of an appropriate scanner setting. To increase the amount of ...
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
As the capture and analysis of single-time-point microarray expression data becomes routine, investigators are turning to time-series expression data to investigate complex gene r...
Selnur Erdal, Ozgur Ozturk, David L. Armbruster, H...