We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Background: Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomic...
Markus Brameier, Josien Haan, Andrea Krings, Rober...
Botnets are networks of compromised computers infected with malicious code that can be controlled remotely under a common command and control (C&C) channel. Recognized as one ...
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Background: Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is...
Euan A. Adie, Richard R. Adams, Kathryn L. Evans, ...