PMID- 24885957
OWN - NLM
STAT- MEDLINE
DCOM- 20140810
LR  - 20211021
IS  - 1471-2105 (Electronic)
IS  - 1471-2105 (Linking)
VI  - 15
DP  - 2014 May 10
TI  - MEIGO: an open-source software suite based on metaheuristics for global 
      optimization in systems biology and bioinformatics.
PG  - 136
LID - 10.1186/1471-2105-15-136 [doi]
AB  - BACKGROUND: Optimization 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. RESULTS: We 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. CONCLUSIONS: MEIGO 
      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.
FAU - Egea, Jose A
AU  - Egea JA
FAU - Henriques, David
AU  - Henriques D
FAU - Cokelaer, Thomas
AU  - Cokelaer T
FAU - Villaverde, Alejandro F
AU  - Villaverde AF
FAU - MacNamara, Aidan
AU  - MacNamara A
FAU - Danciu, Diana-Patricia
AU  - Danciu DP
FAU - Banga, Julio R
AU  - Banga JR
AD  - (Bio)Process Engineering Group, Spanish National Research Council, IIM-CSIC, 
      36208 Vigo, Spain. julio@iim.csic.es.
FAU - Saez-Rodriguez, Julio
AU  - Saez-Rodriguez J
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20140510
PL  - England
TA  - BMC Bioinformatics
JT  - BMC bioinformatics
JID - 100965194
SB  - IM
MH  - Algorithms
MH  - Bayes Theorem
MH  - Computational Biology/*methods
MH  - Metabolic Engineering
MH  - Proteomics
MH  - *Software
MH  - Systems Biology/*methods
PMC - PMC4025564
EDAT- 2014/06/03 06:00
MHDA- 2014/08/12 06:00
PMCR- 2014/05/10
CRDT- 2014/06/03 06:00
PHST- 2013/10/23 00:00 [received]
PHST- 2014/04/24 00:00 [accepted]
PHST- 2014/06/03 06:00 [entrez]
PHST- 2014/06/03 06:00 [pubmed]
PHST- 2014/08/12 06:00 [medline]
PHST- 2014/05/10 00:00 [pmc-release]
AID - 1471-2105-15-136 [pii]
AID - 10.1186/1471-2105-15-136 [doi]
PST - epublish
SO  - BMC Bioinformatics. 2014 May 10;15:136. doi: 10.1186/1471-2105-15-136.