Abstract
Systems Biology has established numerous approaches for mechanistic modelling of molecular networks in the cell and a legacy of models. The current frontier is the integration of models expressed in different formalisms to address the multi-scale biological system organisation challenge. We present MUFINS software, implementing a unique set of approaches for multiformalism simulation of interaction networks. We extend the constraint-based modelling (CBM) framework by incorporation of linear inhibition constraints, enabling for the first time linear modelling of networks simultaneously describing gene regulation, signalling and whole-cell metabolism at steady state. We present a use case where a logical hypergraph model of a regulatory network is expressed by linear constraints and integrated with a Genome Scale Metabolic Network (GSMN) of mouse macrophage. We experimentally validate predictions, demonstrating application of our software in an iterative cycle of hypothesis generation, validation and model refinement. MUFINS incorporates an extended version of our Quasi Steady State Petri Net approach to integrate dynamic models with CBM, which we demonstrate through a dynamic model of cortisol signalling integrated with the human Recon2 GSMN and a model of nutrient dynamics in physiological compartments. Finally, we implement a number of methods for deriving metabolic states from ~omics data, including our new variant of the iMAT congruency approach. We compare our approach with iMAT through analysis of 262 individual tumour transcriptomes, recovering features of metabolic reprogramming in cancer. The software provides graphics user interface with network visualisation, which facilitates use by researchers who are not experienced in coding and mathematical modelling environments.