Background: Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combin...
Fan Shi, Gad Abraham, Christopher Leckie, Izhak Ha...
Background: With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across...
Hyungwon Choi, Ronglai Shen, Arul M. Chinnaiyan, D...
Using microarray technology for genetic analysis in biological experiments requires computationally intensive tools to interpret results. The main objective here is to develop a â...
Saira Ali Kazmi, Yoo-Ah Kim, Baikang Pei, Ravi Nor...
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...