Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
Background: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often ...
Barbara Di Camillo, Fatima Sanchez-Cabo, Gianna To...
Reconstructing networks from time series data is a difficult inverse problem. We apply two methods to this problem using co-temporal functions. Co-temporal functions capture mathe...
Edward E. Allen, Anthony Pecorella, Jacquelyn S. F...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...