We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we cal...
David Heckerman, Dan Geiger, David Maxwell Chicker...
In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three ma...
Shawn Martin, George Davidson, Elebeoba E. May, Je...
: The exponential growth in the quantity of publicly available genetic data and the proliferation of bioinformatic databases mean that scientists need computerized tools more than ...
Bob Myers, Trevor I. Dix, Ross L. Coppel, David G....
Interest is rapidly growing in internationalized software that can be localized to various languages. This paper describes IDUX, an XML-based system designed to support the proces...
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...