In this paper we present a methodology to estimate rates of enzymatic reactions in metabolic pathways. Our methodology is based on applying stochastic logic learning in ensemble le...
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
This paper develops a mathematical characterisation of object-oriented concepts by defining an observation-oriented semantics for an object-oriented language (OOL) with a rich var...
—This paper makes two contributions towards the logical modelling of inhibition in metabolic networks. First it exposes the logical inconsistency of an existing state-of-the-art ...
Background: Expression array data are used to predict biological functions of uncharacterized genes by comparing their expression profiles to those of characterized genes. While b...