Computational tools and resources for integrative modeling in systems biology

Abstract

Mathematical modeling is key for systems level understanding of cellular processes. The development of mathematical models demands advanced computational tools that keep track of heterogeneous data of molecules and their interactions. Especially the integration of experimental data and pre-existing knowledge into computational models of biological systems is of considerable importance. In silico simulations of model behavior under similar conditions as in the experiment give the possibility for model validation regarding specific experimental data. Such an integrative approach leads eventually to a more accurate and consistent description of the observed biological system. We review several resources and computational tools which support the investigation of biological networks and describe several resources and methods for integrative modeling.