## Abstract

We consider the problem of inferring a biological network from given experimental data. In earlier work on metabolic pathway inference, we studied a situation where the molecular interactions were fairly well known, the kinetic parameters were completely unknown and the network topology was almost known. Starting from a similar setting, using simulations, we have investigated the inference
of missing links in a network. We use two approaches, a deterministic one using ordinary differential
equations and one employing a statistical approach. We find that the deterministic fit-based approach yields quite positive results in linear as well as in a non-linear context.

Original language | English |
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Pages | 42-45 |

Publication status | Published - 2013 |