ArticleBioinformatics (Oxford, England)2018
PyDREAM: high-dimensional parameter inference for biological models in python.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
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- Benchmarking Diffusion Annealing-Based Bayesian Inverse Problem Solvers.IEEE open journal of signal processing · 2025Article
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- The tumor microenvironment shows a hierarchy of cell-cell interactions dominated by fibroblasts.Nature communications · 2023Article
- Model certainty in cellular network-driven processes with missing data.PLoS computational biology · 2023Article
- A biochemical necroptosis model explains cell-type-specific responses to cell death cues.Biophysical journal · 2023Article
- Concepts of multi-level dynamical modelling: understanding mechanisms of squamous cell carcinoma development in Fanconi anemia.Frontiers in genetics · 2023Article
- SBbadger: biochemical reaction networks with definable degree distributions.Bioinformatics (Oxford, England) · 2022Article
- Bayesian parameter estimation for dynamical models in systems biology.PLoS computational biology · 2022Article
- 'Neighbourhood watch' model: embryonic epiblast cells assess positional information in relation to their neighbours.Development (Cambridge, England) · 2022Article
- Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit.Bioinformatics (Oxford, England) · 2022Article
- Programmatic modeling for biological systems.Current opinion in systems biology · 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
- Predictive modeling of parafoveal information processing during reading.Scientific reports · 2021Article
- Unsupervised logic-based mechanism inference for network-driven biological processes.PLoS computational biology · 2021Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
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3 authors.
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Abstract
Summary: Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis [DREAM(ZS)] algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012). PyDREAM achieves excellent performance for complex, parameter-rich models and takes full advantage of distributed computing resources, facilitating parameter inference and uncertainty estimation of CPU-intensive biological models. Availability and implementation: PyDREAM is freely available under the GNU GPLv3 license from the Lopez lab GitHub repository at http://github.com/LoLab-VU/PyDREAM. Contact: c.lopez@vanderbilt.edu. Supplementary information: Supplementary data are available at Bioinformatics online.
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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 Socratic graph.