Background: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), i...
Peter D. Wentzell, Tobias K. Karakach, Sushmita Ro...
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
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: Biochemical investigations over the last decades have elucidated an increasingly complete image of the cellular metabolism. To derive a systems view for the regulation...
Gunnar Schramm, Marc Zapatka, Roland Eils, Rainer ...
Background: One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public re...
Kyu Baek Hwang, Sek Won Kong, Steven A. Greenberg,...