ArticleNPJ systems biology and applications2016
MUFINS: multi-formalism interaction network simulator.
Article in NPJ systems biology and applications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- Cyclone: open-source package for simulation and analysis of finite dynamical systems.Bioinformatics (Oxford, England) · 2023Article
- Hybrid modelling of biological systems: current progress and future prospects.Briefings in bioinformatics · 2022Review
- Advances in flux balance analysis by integrating machine learning and mechanism-based models.Computational and structural biotechnology journal · 2021Review
- PlantSimLab - a modeling and simulation web tool for plant biologists.BMC bioinformatics · 2019Article
- Circadian regulation in human white adipose tissue revealed by transcriptome and metabolic network analysis.Scientific reports · 2019Article
- Systems Biology Approaches Toward Understanding Primary Mitochondrial Diseases.Frontiers in genetics · 2019Review
- Multi-scale, whole-system models of liver metabolic adaptation to fat and sugar in non-alcoholic fatty liver disease.NPJ systems biology and applications · 2018Article
- Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation.NPJ systems biology and applications · 2018Article
- Linking physiologically-based pharmacokinetic and genome-scale metabolic networks to understand estradiol biology.BMC systems biology · 2017Article
- Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics.CPT: pharmacometrics & systems pharmacology · 2017Article
Corrections and comments
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Authors and funding
20 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.