ArticleBMC bioinformatics2014
MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed.
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- Deciphering Metabolic Pathways in High-Seeding-Density Fed-Batch Processes for Monoclonal Antibody Production: A Computational Modeling Perspective.Bioengineering (Basel, Switzerland) · 2024Article
- A multi-scale digital twin for adiposity-driven insulin resistance in humans: diet and drug effects.Diabetology & metabolic syndrome · 2023Article
- IDESS: a toolbox for identification and automated design of stochastic gene circuits.Bioinformatics (Oxford, England) · 2023Article
- Automated Design of Synthetic Gene Circuits in the Presence of Molecular Noise.ACS synthetic biology · 2023Article
- Optimal evaluation of energy yield and driving force in microbial metabolic pathway variants.PLoS computational biology · 2023Article
- A comprehensive mechanistic model of adipocyte signaling with layers of confidence.NPJ systems biology and applications · 2023Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundOptimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools.
resultsWe present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods.
conclusionsMEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods.
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