Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
Discovering patterns or frequent episodes in transactions is an important problem in data-mining for the purpose of infering deductive rules from them. Because of the huge size of...
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work by Sang, Beame, and Kautz (AAAI 200...
In this paper we describe the development of an ontology of molecular and phenotypic cereals data, realized by integrating existing public web databases with the database developed...