MEIGO

 

MEIGO is a global optimization toolbox that includes a number of metaheuristic methods as well as (currently in the R version only) a Bayesian inference method for parameter estimation. They can be used to solve the following problem classes:

• nonlinear programming (NLP) and mixed-integer nonlinear programming (MINLP) using the enhanced scatter search metaheuristic (eSS [1]).
• combinatorial (binary and integer programming) optimization problems using the variable neighbourhood metaheuristic (VNS [2]).
• continuous parameter estimation using the Bayesian inference method BayesFit (R version only), based in ref [5].

Examples of these problem classes in bioinformatics and systems biology are:

• parameter estimation in static and dynamic biology models
• network inference
• optimal experimental design
• metabolic engineering
• optimal design of synthetic biological networks
• sequence alignment
• genome rearrangement
• protein structure prediction

In order to facilitate its use and interfacing with other software packages, we provide:

• Matlab implementations (eSS, VNS)
• R implementations (eSSR, VNSR, BayesFit)
• Python interface to the R implementations

Furthermore, we also provide parallel implementations of these solvers based on a cooperative strategy [3]:

• cooperative parallel eSS (CeSS, in Matlab, and CeSSR, in R)
• cooperative parallel VNS (CVNS, in Matlab, and CVNSR, in R)

If you want to cite MEIGO, please use ref [4] below.

Related publications

[1] Egea, J.A., Martí, R. and Banga, J.R. (2010) An evolutionary method for complex-process optimization. Computers and Operations Research, 37(2), 315-324.

[2] Hansen, P.. Mladenović, N. and Moreno Pérez, J.A. (2010) Variable neighborhood search: methods and applications. Annals of Operations Research, 175, 367–407.

[3] Villaverde, A.F., Egea, J.A. and Banga, J.R. (2012) A cooperative strategy for param-eter estimation in large scale systems biology models. BMC Systems Biology, 6:75.

[4] Egea JA, Henriques D, Cokelaer T, Villaverde AF, MacNamara A, Danciu DP, Banga JR and Saez-Rodriguez J. (2014) MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics. BMC Bioinformatics 15:136.
(article)

[5] Eydgahi, H., Chen, W. W., Muhlich, J. L., Vitkup, D., Tsitsiklis, J. N. and Sorger, P. K. (2013). Properties of cell death models calibrated and compared using Bayesian approaches. Molecular Systems Biology 9(1).