Background: Elucidating the dynamic behaviour of genetic regulatory networks is one of the most significant challenges in systems biology. However, conventional quantitative predi...
Users of topic modeling methods often have knowledge about the composition of words that should have high or low probability in various topics. We incorporate such domain knowledg...
—This paper describes a new logic-based approach for representing and reasoning about metabolic networks. First it shows how biological pathways can be elegantly represented in a...
We describe the underlying probabilistic generative signal model of non-negative matrix factorisation (NMF) and propose a realistic conjugate priors on the matrices to be estimate...
Tuomas Virtanen, Ali Taylan Cemgil, Simon J. Godsi...
In this paper we present how to estimate a continuous space Language Model with a Neural Network to be used in a Statistical Machine Translation system. We report results for an I...