ArticleBioinformatics (Oxford, England)2016
BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- The Constrained Disorder Principle Overcomes the Challenges of Methods for Assessing Uncertainty in Biological Systems.Journal of personalized medicine · 2024Review
- BioNetGMMFit: estimating parameters of a BioNetGen model from time-stamped snapshots of single cells.NPJ systems biology and applications · 2023Article
- SBbadger: biochemical reaction networks with definable degree distributions.Bioinformatics (Oxford, England) · 2022Article
- Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit.Bioinformatics (Oxford, England) · 2022Article
- Relating simulation studies by provenance-Developing a family of Wnt signaling models.PLoS computational biology · 2021Article
- Modeling the Nonlinear Dynamics of Intracellular Signaling Networks.Bio-protocol · 2021Article
- Revealing dynamic regulations and the related key proteins of myeloma-initiating cells by integrating experimental data into a systems biological model.Bioinformatics (Oxford, England) · 2021Article
- Bayesian inference using qualitative observations of underlying continuous variables.Bioinformatics (Oxford, England) · 2020Article
- Multisite EGFR phosphorylation is regulated by adaptor protein abundances and dimer lifetimes.Molecular biology of the cell · 2020Article
- Pleione: A tool for statistical and multi-objective calibration of Rule-based models.Scientific reports · 2019Article
- Article
- Scaling methods for accelerating kinetic Monte Carlo simulations of chemical reaction networks.The Journal of chemical physics · 2019Article
- Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor.PLoS computational biology · 2019Article
- Intrinsic limits of information transmission in biochemical signalling motifs.Interface focus · 2018Article
- Using both qualitative and quantitative data in parameter identification for systems biology models.Nature communications · 2018Article
- Evaluation of Parallel Tempering to Accelerate Bayesian Parameter Estimation in Systems Biology.Proceedings. Euromicro International Conference on Parallel, Distributed, and Network-based Processing · 2018Article
- PyDREAM: high-dimensional parameter inference for biological models in python.Bioinformatics (Oxford, England) · 2018Article
- From word models to executable models of signaling networks using automated assembly.Molecular systems biology · 2017Article
- Timescale Separation of Positive and Negative Signaling Creates History-Dependent Responses to IgE Receptor Stimulation.Scientific reports · 2017Article
- Quantitative computational models of molecular self-assembly in systems biology.Physical biology · 2017Review
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Authors and funding
7 authors.
Funding
Abstract
unlabelledRule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. AVAILABILITY AND IMPLEMENTATION: BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: bionetgen.help@gmail.com.
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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.