Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much ...
Benjamin Chain, Helen Bowen, John Hammond, Wilfrie...
We present a robust method for time-frequency model estimation. It involves a robust Leclerc's estimator to ensure robustness w.r.t. noise and interferences present in timefr...
Ronan Fablet, Abdessalam Benzinou, Christian Donca...
This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our desig...