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dc.contributor.authorColomer, M. Àngels (Maria Àngels)
dc.contributor.authorMargalida, Antoni
dc.contributor.authorPérez Jiménez, Mario de Jesús
dc.description.abstractToday, the volume of data and knowledge of processes necessitates more complex models that integrate all available information. This handicap has been solved thanks to the technological advances in both software and hardware. Computational tools available today have allowed developing a new family of models, known as computational models. The description of these models is difficult as they can not be expressed analytically, and it is therefore necessary to create protocols that serve as guidelines for future users. The Population Dynamics P systems models (PDP) are a novel and effective computational tool to model complex problems, are characterized by the ability to work in parallel (simultaneously interrelating different processes), are modular and have a high computational efficiency. However, the difficulty of describing these models therefore requires a protocol to unify the presentation and the steps to follow. We use two case studies to demonstrate the use and implementation of these computational models for population dynamics and ecological process studies, discussing briefly their potential applicability to simulate complex ecosystem dynamics.ca_ES
dc.description.sponsorshipThe authors acknowledge the support of the Spanish Network on Biomolecular and Biocellular Computing TIN2008-04487-E of the Ministerio de Ciencia e Inovación of Spain. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
dc.publisherPublic Library of Science (PLoS)ca_ES
dc.relation.isformatofReproducció del document publicat a
dc.relation.ispartofPLoS ONE, 2013, vol. 8, núm. 4, e60698ca_ES
dc.rightscc-by, (c) Colomer et al., 2013ca_ES
dc.subject.otherVoltors -- Conservacióca_ES
dc.subject.otherBiologia computacionalca_ES
dc.titlePopulation Dynamics P system (PDP) models: a standarized protocol for describing and applying novel bio-inspires computing toolsca_ES

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