In this paper we propose a method to derive OCL invariants from declarative model-to-model transformations in order to enable their verification and analysis. For this purpose we ...
This paper presents an alternative to distance-based neural networks. A distance measure is the underlying property on which many neural models rely, for example self-organizing ma...
Background: Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved se...
Abstract— In this paper, we develop methods to “sample” a large real network into a small realistic graph. Although topology modeling has received a lot attention lately, it ...
Background: Visualising the evolutionary history of a set of sequences is a challenge for molecular phylogenetics. One approach is to use undirected graphs, such as median network...