The informative value of biomolecular networks has shifted from being solely information resources for possible cellular partners (whether these embody proteins, (ribo)nucleic aci...
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
We apply evolutionary computation to calibrate the parameters of a morphogenesis model of Drosophila early development. The model aims to describe the establishment of the steady g...
The issue of initializing the model of a new student is of great importance for educational applications that aim at offering individualized support to students. In this paper we ...
Many algorithms developed in computational geometry are needlessly complicated and slow because they have to be prepared for very complicated, hypothetical inputs. To avoid this, ...
Mark de Berg, Matthew J. Katz, A. Frank van der St...