Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Background: Reverse-engineering regulatory networks is one of the central challenges for computational biology. Many techniques have been developed to accomplish this by utilizing...
Shawn Cokus, Sherri Rose, David Haynor, Niels Gr&o...
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
A model for reference use in communication is proposed, from a representationist point of view. Both the sender and the receiver of a message handle representations of their commo...
e is an aspect-oriented hardware verification language that is widely used to verify the design of electronic circuits through the development and execution of testbenches. In rec...