Background: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little ov...
Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Ha...
In this paper we aim to infer a model of genetic networks from time series data of gene expression profiles by using a new gene expression programming algorithm. Gene expression n...
Background: The accurate detection of differentially expressed (DE) genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variabi...
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
We address the problem of using expression data and prior biological knowledge to identify differentially expressed pathways or groups of genes. Following an idea of Ideker et al...
Serban Nacu, Rebecca Critchley-Thorne, Peter Lee, ...