: Recently lots of studies aim at modeling and inferring gene networks. Modeling tools propose graphical models having almost nothing about time description of events and regards t...
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...
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
Representing articulated objects as a graphical model has gained much popularity in recent years, often the root node of the graph describes the global position and orientation of...
Background: With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these mol...