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dc.contributor.authorMartin, Alberto J. M. [Univ Mayor, Fac Ciencias, Network Biol Lab, Ctr Genom & Bioinformat]es_CL
dc.contributor.authorSantibáñez, Rodrigo [Univ Mayor, Fac Ciencias, Network Biol Lab, Ctr Genom & Bioinformat]es_CL
dc.contributor.authorGarrido, Danieles_CL
dc.date.accessioned2020-04-12T14:11:55Z
dc.date.accessioned2020-04-14T15:37:54Z
dc.date.available2020-04-12T14:11:55Z
dc.date.available2020-04-14T15:37:54Z
dc.date.issued2019es_CL
dc.identifier.citationSantibáñez, R., Garrido, D., & Martin, A. J. (2019). Pleione: A tool for statistical and multi-objective calibration of Rule-based models. Scientific reports, 9(1), 1-13.es_CL
dc.identifier.issn2045-2322es_CL
dc.identifier.urihttps://doi.org/10.1038/s41598-019-51546-6es_CL
dc.identifier.urihttps://www.nature.com/articles/s41598-019-51546-6es_CL
dc.identifier.urihttp://repositorio.umayor.cl/xmlui/handle/sibum/6558
dc.description.abstractMathematical models based on Ordinary Differential Equations (ODEs) are frequently used to describe and simulate biological systems. Nevertheless, such models are often difficult to understand. Unlike ODE models, Rule-Based Models (RBMs) utilise formal language to describe reactions as a cumulative number of statements that are easier to understand and correct. They are also gaining popularity because of their conciseness and simulation flexibility. However, RBMs generally lack tools to perform further analysis that requires simulation. This situation arises because exact and approximate simulations are computationally intensive. Translating RBMs into ODEs is commonly used to reduce simulation time, but this technique may be prohibitive due to combinatorial explosion. Here, we present the software called Pleione to calibrate RBMs. Parameter calibration is essential given the incomplete experimental determination of reaction rates and the goal of using models to reproduce experimental data. The software distributes stochastic simulations and calculations and incorporates equivalence tests to determine the fitness of RBMs compared with data. The primary features of Pleione were thoroughly tested on a model of gene regulation in Escherichia coli. Pleione yielded satisfactory results regarding calculation time and error reduction for multiple simulators, models, parameter search strategies, and computing infrastructures.es_CL
dc.description.sponsorshipCONICYTComision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) [PCHA/Doctorado Nacional/2014-21140377]; Fondecyt RegularComision Nacional de Investigacion Cientifica y Tecnologica (CONICYT)CONICYT FONDECYT [1181089]; CYTED project [P918PTE0261]; NLHPC [ECM-02]es_CL
dc.description.sponsorshipWe acknowledge the help received from Dr Maria Rodriguez and Dr Pedro Saa for discussion about calibration methods and evaluation functions. This research was funded by CONICYT grants PCHA/Doctorado Nacional/2014-21140377 to RS; Fondecyt Regular 1181089 and CYTED project P918PTE0261 to AJMM. Powered@NLHPC: This research was partially supported by the supercomputing infrastructure of the NLHPC (ECM-02).es_CL
dc.language.isoenes_CL
dc.publisherNATURE PUBLISHING GROUPes_CL
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.sourceSci Rep, OCT, 2019. 9
dc.subjectMultidisciplinary Scienceses_CL
dc.titlePleione: A tool for statistical and multi-objective calibration of Rule-based modelses_CL
dc.typeArtículoes_CL
umayor.facultadCIENCIAS
umayor.politicas.sherpa/romeoDOAJ Gold, Green Publishedes_CL
umayor.indexadoWOS:000491306300004es_CL
umayor.indexadoPMID: 31641245es_CL
dc.identifier.doiDOI: 10.1038/s41598-019-51546-6es_CL]
umayor.indicadores.wos-(cuartil)Q3es_CL
umayor.indicadores.scopus-(scimago-sjr)SCIMAGO/ INDICE H: 49 Hes_CL


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