Background: Reverse-engineering regulatory networks is one of the central challenges for computational biology. Many techniques have been developed to accomplish this by utilizing...
Shawn Cokus, Sherri Rose, David Haynor, Niels Gr&o...
Background: Modeling cancer-related regulatory modules from gene expression profiling of cancer tissues is expected to contribute to our understanding of cancer biology as well as...
Background: This work explores the quantitative characteristics of the local transcriptional regulatory network based on the availability of time dependent gene expression data se...
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...
Background: Functional genomics studies are yielding information about regulatory processes in the cell at an unprecedented scale. In the yeast S. cerevisiae, DNA microarrays have...