ArticleBMC systems biology2015
BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology.
Article in BMC systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guidelines for benchmarking of optimization-based approaches for fitting mathematical models.Genome biology · 2019Guideline
- The Dawn of High-Throughput and Genome-Scale Kinetic Modeling: Recent Advances and Future Directions.ACS synthetic biology · 2025Review
- Benchmarking methods for computing local sensitivities in ordinary differential equation models at dynamic and steady states.PloS one · 2024Article
- A bistable autoregulatory module in the developing embryo commits cells to binary expression fates.Current biology : CB · 2023Article
- SBbadger: biochemical reaction networks with definable degree distributions.Bioinformatics (Oxford, England) · 2022Article
- Fides: Reliable trust-region optimization for parameter estimation of ordinary differential equation models.PLoS computational biology · 2022Article
- Kinetic Modeling ofMetabolites · 2022Review
- Relationship Between Dimensionality and Convergence of Optimization Algorithms: A Comparison Between Data-Driven Normalization and Scaling Factor-Based Methods Using PEPSSBI.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Benchmark problems for dynamic modeling of intracellular processes.Bioinformatics (Oxford, England) · 2019Article
- Benchmarking optimization methods for parameter estimation in large kinetic models.Bioinformatics (Oxford, England) · 2019Article
- Sensitivity analysis for reproducible candidate values of model parameters in signaling hub model.PloS one · 2019Article
- Dynamic Optimization with Particle Swarms (DOPS): a meta-heuristic for parameter estimation in biochemical models.BMC systems biology · 2018Article
- Tellurium: An extensible python-based modeling environment for systems and synthetic biology.Bio Systems · 2018Article
- Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis.Bioinformatics (Oxford, England) · 2018Article
- In silico cancer research towards 3R.BMC cancer · 2018Review
- Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems.BMC systems biology · 2017Article
- Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems.BMC systems biology · 2017Article
- Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.BMC bioinformatics · 2017Article
- Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks.PLoS computational biology · 2017Article
- Performance of objective functions and optimisation procedures for parameter estimation in system biology models.NPJ systems biology and applications · 2017Article
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13 authors.
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Abstract
backgroundDynamic modelling is one of the cornerstones of systems biology. Many research efforts are currently being invested in the development and exploitation of large-scale kinetic models. The associated problems of parameter estimation (model calibration) and optimal experimental design are particularly challenging. The community has already developed many methods and software packages which aim to facilitate these tasks. However, there is a lack of suitable benchmark problems which allow a fair and systematic evaluation and comparison of these contributions.
resultsHere we present BioPreDyn-bench, a set of challenging parameter estimation problems which aspire to serve as reference test cases in this area. This set comprises six problems including medium and large-scale kinetic models of the bacterium E. coli, baker's yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The level of description includes metabolism, transcription, signal transduction, and development. For each problem we provide (i) a basic description and formulation, (ii) implementations ready-to-run in several formats, (iii) computational results obtained with specific solvers, (iv) a basic analysis and interpretation.
conclusionsThis suite of benchmark problems can be readily used to evaluate and compare parameter estimation methods. Further, it can also be used to build test problems for sensitivity and identifiability analysis, model reduction and optimal experimental design methods. The suite, including codes and documentation, can be freely downloaded from the BioPreDyn-bench website, https://sites.google.com/site/biopredynbenchmarks/ .
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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.