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...
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Stochastic analysis techniques for real-time systems model the execution time of tasks as random variables. These techniques constitute a very powerful tool to study the behaviour...
Genetic anticipation for a particular disease can involve an earlier age at onset (or, diagnosis), greater severity, and/or a higher number of affected individuals in successive g...
Gleb R. Haynatzki, Randall E. Brand, Vera R. Hayna...
Constructing models of systems that change their structure over time has proved to be a challenging problem, with several proposed solutions. We present two of these approaches an...
Fernando J. Barros, Bernard P. Zeigler, Paul A. Fi...