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A Microbial Screening in Silico Method for the Fitness Step Evaluation in Evolutionary Algorithms

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dc.contributor.authorGargantilla Becerra, A.
dc.contributor.authorLahoz Beltrá, Rafael
dc.date.accessioned2023-06-17T09:12:30Z
dc.date.available2023-06-17T09:12:30Z
dc.date.issued2020-06-05
dc.description.abstractOne of the most delicate stages of an evolutionary algorithm is the evaluation of the goodness of the solutions by some procedure providing a fitness value. However, although there are general rules, it is not always easy to find an appropriate evaluation function for a given problem. In the biological realm, today, there is a variety of experimental methods under the name of microbial screening to identify and select bacteria from their traits, as well as to obtain their fitness. In this paper, we show how given an optimization problem, a colony of synthetic bacteria or bacterial agents is able to evaluate the fitness of candidate solutions by building an evaluation function. The evaluation function is obtained simulating, in silico, a bacterial colony conducting the laboratory methods used in microbiology, biotechnology and synthetic biology to measure microbial fitness. Once the evaluation function is built, it is included in the code of the genetic algorithm as part of the fitness routine. The practical use of this approach is illustrated in two classic optimization problems. In silico routines have been programmed in Gro, a cell programming language oriented to synthetic biology, and can easily be customized to many other optimization problems.
dc.description.departmentDepto. de Biodiversidad, Ecología y Evolución
dc.description.facultyFac. de Ciencias Biológicas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/67567
dc.identifier.doi10.3390/app10113936
dc.identifier.issn2076-3417
dc.identifier.officialurlhttps://www.mdpi.com/2076-3417/10/11/3936
dc.identifier.urihttps://hdl.handle.net/20.500.14352/8396
dc.issue.number11
dc.journal.titleApplied Sciences
dc.language.isoeng
dc.page.initial3936
dc.publisherMDPI
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.cdu51:57
dc.subject.keywordEvolutionary computing
dc.subject.keywordFitness function evaluation
dc.subject.keywordBioinspired algorithms
dc.subject.keywordSynthetic biology
dc.subject.ucmBiomatemáticas
dc.subject.unesco2404 Biomatemáticas
dc.titleA Microbial Screening in Silico Method for the Fitness Step Evaluation in Evolutionary Algorithms
dc.typejournal article
dc.volume.number10
dspace.entity.typePublication
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