MUFINS: multi-formalism interaction network simulator.

Nilgun Sahin,Jacek Sroka,Lara Ward ,Steffen Klamt,David Lewis ,Hans V. Westerhoff ,Ahmad A. Mannan ,Catherine Linley,Axel von Kamp,Graham R. Stewart ,Huihai Wu,Nicholas Stoy,Vytautas Leoncikas,Nick Plant ,Hiroshi Matsuo ,Andrzej M. Kierzek ,Johnjoe McFadden,Albert Gevorgyan,M. Grabowski ,Wataru Mori

doi:10.1038/npjsba.2016.32

Abstract

Systems Biology has established numerous approaches for mechanistic modeling 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 organization challenge. We present MUFINS (MUlti-Formalism Interaction Network Simulator) software, implementing a unique set of approaches for multi-formalism simulation of interaction networks. We extend the constraint-based modeling (CBM) framework by incorporation of linear inhibition constraints, enabling for the first time linear modeling of networks simultaneously describing gene regulation, signaling 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 signaling 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 the analysis of 262 individual tumor transcriptomes, recovering features of metabolic reprogramming in cancer. The software provides graphics user interface with network visualization, which facilitates use by researchers who are not experienced in coding and mathematical modeling environments.

Highlights

During the last two decades, Systems Biology has established numerous approaches to represent molecular biology knowledge in the form of mechanistic molecular interaction network models
Modeling of large-scale gene regulatory and signaling networks is much more challenging and a number of qualitative simulation approaches have been formulated, such as analysis of steady states in logical hypergraphs,[6] enumeration of states in dynamic Boolean models,[7] Monte Carlo exploration of the alternative molecular transition sequences constrained by network connectivity expressed in Petri Net formalism.[8,9]
We present MUFINS (MUlti-Formalism Interaction Network Simulator) software and argue that it is the first general software with Graphics User Interface (GUI) capable of integrating models developed in all major modeling frameworks of Computational Systems Biology

Summary

Introduction

During the last two decades, Systems Biology has established numerous approaches to represent molecular biology knowledge in the form of mechanistic molecular interaction network models. We present MUFINS (MUlti-Formalism Interaction Network Simulator) software and argue that it is the first general software with Graphics User Interface (GUI) capable of integrating models developed in all major modeling frameworks of Computational Systems Biology.

Results

Conclusion