Stefano Schivo, Jetse Scholma, Marcel Karperien, Janine Post, Jaco van der Pol, Rom Langerak

Proceedings 1st International Workshop on Synthesis of Continuous Parameters - 2014

Abstract

ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g.

signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of

interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the

parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior

of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general,

the topology of a model can be expanded with new (known or hypothetical) nodes, and enables it to match experimental

data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex

too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model

unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit

as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support

added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the

parameter settings.