ArticleBMC bioinformatics2010
Odefy--from discrete to continuous models.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed.
- Data-driven inference of Boolean networks from transcriptomes to predict cellular differentiation and reprogramming.NPJ systems biology and applications · 2025Article
- Logic-based modeling of inflammatory macrophage cross talk with glomerular endothelial cells in diabetic kidney disease.American journal of physiology. Renal physiology · 2025Article
- The dawn of a new era: can machine learning and large language models reshape QSP modeling?Journal of pharmacokinetics and pharmacodynamics · 2025Review
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- A yeast cell cycle pulse generator model shows consistency with multiple oscillatory and checkpoint mutant datasets.Mathematical biosciences · 2024Article
- Assessing biological network dynamics: comparing numerical simulations with analytical decomposition of parameter space.NPJ systems biology and applications · 2023Article
- Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments.Scientific reports · 2022Article
- From data to QSP models: a pipeline for using Boolean networks for hypothesis inference and dynamic model building.Journal of pharmacokinetics and pharmacodynamics · 2022Article
- Cluster Gauss-Newton and CellNOpt Parameter Estimation in a Small Protein Signaling Network of Vorinostat and Bortezomib Pharmacodynamics.The AAPS journal · 2021Article
- Network-Based Systems Analysis Explains Sequence-Dependent Synergism of Bortezomib and Vorinostat in Multiple Myeloma.The AAPS journal · 2021Article
- Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks.Science advances · 2021Article
- Multiscale Regulation of the Intervertebral Disc: Achievements in Experimental, In Silico, and Regenerative Research.International journal of molecular sciences · 2021Review
- Mathematical Modelling in Biomedicine: A Primer for the Curious and the Skeptic.International journal of molecular sciences · 2021Review
- Systems Pharmacology Modeling Identifies a Novel Treatment Strategy for Bortezomib-Induced Neuropathic Pain.Frontiers in pharmacology · 2021Article
- Biological Regulatory Network (BRN) Analysis and Molecular Docking Simulations to Probe the Modulation of IPGenes · 2020Article
- Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling.Frontiers in genetics · 2020Review
- Identifying (un)controllable dynamical behavior in complex networks.PLoS computational biology · 2018Article
- Network-Based Analysis of Bortezomib Pharmacodynamic Heterogeneity in Multiple Myeloma Cells.The Journal of pharmacology and experimental therapeutics · 2018Article
- Boolean network modeling in systems pharmacology.Journal of pharmacokinetics and pharmacodynamics · 2018Review
- Simulation of the Dynamics of Primary Immunodeficiencies in B Cells.Frontiers in immunology · 2018Article
Corrections and comments
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPhenomenological information about regulatory interactions is frequently available and can be readily converted to Boolean models. Fully quantitative models, on the other hand, provide detailed insights into the precise dynamics of the underlying system. In order to connect discrete and continuous modeling approaches, methods for the conversion of Boolean systems into systems of ordinary differential equations have been developed recently. As biological interaction networks have steadily grown in size and complexity, a fully automated framework for the conversion process is desirable.
resultsWe present Odefy, a MATLAB- and Octave-compatible toolbox for the automated transformation of Boolean models into systems of ordinary differential equations. Models can be created from sets of Boolean equations or graph representations of Boolean networks. Alternatively, the user can import Boolean models from the CellNetAnalyzer toolbox, GINSim and the PBN toolbox. The Boolean models are transformed to systems of ordinary differential equations by multivariate polynomial interpolation and optional application of sigmoidal Hill functions. Our toolbox contains basic simulation and visualization functionalities for both, the Boolean as well as the continuous models. For further analyses, models can be exported to SQUAD, GNA, MATLAB script files, the SB toolbox, SBML and R script files. Odefy contains a user-friendly graphical user interface for convenient access to the simulation and exporting functionalities. We illustrate the validity of our transformation approach as well as the usage and benefit of the Odefy toolbox for two biological systems: a mutual inhibitory switch known from stem cell differentiation and a regulatory network giving rise to a specific spatial expression pattern at the mid-hindbrain boundary.
conclusionsOdefy provides an easy-to-use toolbox for the automatic conversion of Boolean models to systems of ordinary differential equations. It can be efficiently connected to a variety of input and output formats for further analysis and investigations. The toolbox is open-source and can be downloaded at http://cmb.helmholtz-muenchen.de/odefy.
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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.