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...
Following the framework proposed by Besnard and Hunter for argumentation, this paper aims to propose a logical tool for the generation of new arguments when two formal agents have...
Propositionalization has already been shown to be a particularly promising approach for robustly and effectively handling relational data sets for knowledge discovery. In this pap...
Background: High throughput methods of the genome era produce vast amounts of data in the form of gene lists. These lists are large and difficult to interpret without advanced com...
We describe algorithms for pattern matching and pattern learning in TOPS diagrams (formal descriptions of protein topologies). These problems can be reduced to checking for subgrap...