Qualitative behavior of a coarse-grain growth model

The construction of comprehensive, integrative computational models are of exceptional interest in Systems Biology, since they could help researchers to understand the emergent cellular functions and help physicians to treat diseases. Within this framework, detailed molecular models are usually unmanageable because, besides identifiability problems, even correct simulations may not lead to understanding. On the other hand a multi-scaled, modular flexibly-grained modeling approach would provide an overview for the subsequent molecular details, trying to capture the basic emergent properties associated to each module. This note deals with a minimal model of cellular growth, involving ribosome and protein content. A modified version of the model has been recently implemented as a module of a coarse-grain model combining growth, metabolism and cycle, providing encouraging results for both single cell and population simulations. Here we propose the qualitative behavior analysis of the model, providing model parameters conditions that ensure (or prevent) growth. This way known approximated results are overcome and improved, allowing to infer information about the model qualitative behavior without resorting to numerical simulations.