A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
During the last years, the growing application complexity, design, and mask costs have compelled embedded system designers to increasingly consider partially reconfigurable applica...
The objective is to investigate two emerging information technologies in graduate studies and scientific cooperation. Internet is the first technology. The open source is the secon...
Systemic pathways-oriented approaches to analysis of metabolic networks are effective for small networks but are computationally infeasible for genome scale networks. Current comp...
Nagiza F. Samatova, Al Geist, George Ostrouchov, A...
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...