We introduce a new probability distribution over a potentially infinite number of binary Markov chains which we call the Markov Indian buffet process. This process extends the IBP...
Recent research has demonstrated the strong performance of hidden Markov models applied to information extraction--the task of populating database slots with corresponding phrases...
Background: Most profile and motif databases strive to classify protein sequences into a broad spectrum of protein families. The next step of such database studies should include ...
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...
Information extraction can be defined as the task of automatically extracting instances of specified classes or relations from text. We consider the case of using machine learni...