Background: Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative e...
Deli Wang, Jian Huang, Hehuang Xie, Liliana Manzel...
Ensuring model quality is a key success factor in many computer science areas, and becomes crucial in recent software engineering paradigms like the one proposed by model-driven s...
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Background: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic an...
David M. Mutch, Alvin Berger, Robert Mansourian, A...
Abstract-- Computer architects must determine how to most effectively use finite computational resources when running simulations to evaluate new architectural ideas. To facilitate...