Background: One of main aims of Molecular Biology is the gain of knowledge about how molecular components interact each other and to understand gene function regulations. Using mi...
Pietro Zoppoli, Sandro Morganella, Michele Ceccare...
Bayesian networks (BNs) have been widely used as a model for knowledge representation and probabilistic inferences. However, the single probability representation of conditional d...
— In this paper we address the problem of predicting gene activities by finding gene regulatory dependencies in experimental DNA microarray data. Only few approaches to infer th...
Christian Spieth, Felix Streichert, Nora Speer, Ch...
The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values...
Abstract-- This paper presents a novel framework for integrating fundamental tasks in robotic navigation through a statistical inference procedure. A probabilistic model that joint...