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A model-based approach to selection of tag SNPs Inra
Nicolas, P.; Sun, F.; Li, L.M..
Tipo: Journal Article Palavras-chave: SINGLE-NUCLEOTIDE POLYMORPHISMS; DESCRIPTION-LENGTH PRINCIPLE; GENOME-WIDE ASSOCIATION; LINKAGE DISEQUILIBRIUM; HAPLOTYPE BLOCKS; MATHEMATICAL-THEORY; MAXIMUM-LIKELIHOOD; RECOMBINATION RATE; COMPLEX DISEASE; INFERENCE.
Ano: 2006 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2009fe15e357&uri=/notices/prodinra1/2009/10/
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Accounting for biological variability and sampling scale: a multi-scale approach to building epidemic models Inra
Soubeyrand, S.; Thébaud, G.; Chadoeuf, J..
When one considers the fine-scale spread of an epidemic, one usually knows the sources of biological variability and their qualitative effect on the epidemic process. The force of infection on a susceptible unit depends on the locations and the strengths of the infectious units, and on the environmental and intrinsic factors affecting infectivity and/or susceptibility. The infection probability for the susceptible unit can then be modelled as a function of these factors. Thus, one can build a conceptual model at the fine scale. However, the epidemic is generally observed at a larger scale and one has to build a model adapted to this larger scale. But how can the sources of variation identified at the fine scale be integrated into the model at the larger...
Tipo: Journal Article Palavras-chave: DISPERSION DU POLLEN; DISPERSION STOCHASTIQUE MIXED MODELS; DISEASE SPREAD; INFERENCE; PATTERN; MULTI-SCALE MODELLING; PROPAGULE DISPERSAL; STOCHASTIC DISPERSAL; DISEASE TRANSMISSION; POLLEN DISPERSAL.
Ano: 2007 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD200754ac47a0&uri=/notices/prodinra1/2010/11/
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Infering population history with DIYABC: a user-friendly approach to Approximate Bayesian Computation Inra
Cornuet, J.M.; Santos, F.; Beaumont, M.A.; Robert, C.P.; Marin, J.M.; Balding, D.J.; Guillemaud, T.; Estoup, A..
Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract this information (at least partially) but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIYABC) for inference based on Approximate Bayesian Computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and stepwise population size changes. DIYABC can be used to...
Tipo: Journal Article Palavras-chave: INFERENCE; HISTORY; POPULATION DYNAMICS; POPULATION GENETICS; STATISTICS; MATHEMATICAL PROGRAMMING.
Ano: 2008 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2009bea71fa3&uri=/notices/prodinra1/2011/04/
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Les systèmes d'information géographique : l'outil d'une recherche transdisciplinaire IRD
Delaunay, Daniel.
Trois cartes et un schéma pour illustrer la présentation d'une méthode d'inférence statistique permettant, à l'aide d'un Système d'Information Géographique, la confrontation de géographies distinctes de l'espace, à savoir celles de l'usage du sol, du peuplement et des divisions administratives. (Résumé d'auteur)
Tipo: Text Palavras-chave: SYSTEME D'INFORMATION GEOGRAPHIQUE; SYSTEME AGRAIRE; POPULATION; REPARTITION GEOGRAPHIQUE; DIVISION ADMINISTRATIVE; INFERENCE.
Ano: 1991 URL: http://www.documentation.ird.fr/hor/fdi:37342
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Méthode d'inférence générique avec plusieurs règles implicatives et une entrée floue Inra
Jones, H.; Dubois, D.; Guillaume, S.; Charnomordic, B..
Cet article propose une méthode générique d’inférence avec des règles implicatives graduelles et des entrées floues. Les règles graduelles permettent de représenterdes contraintes sur un ensemble de possibles et sont très intéressantes pour leur capacité d’interpolation. Nousproposons une méthode d’inférence basée sur la notion de système bien conditionné. Elle s’appuie sur l’inférence à partir d’entrées rectangulaires dont le calcul s’avèresimple. Elle utilise une double décomposition : par a-coupes pour se ramener à des entrées rectangulaires et parpartitionnement de ces coupes en régions rectangulaires où seules deux règles s’appliquent à la fois.
Tipo: Conference Paper Palavras-chave: REGLES IMPLICATIVES GRADUELLES; ENTREES FLOUES; INFERENCE; SYSTEME BIEN CONDITIONNE; DECOMPOSITION IMPLICATIVE GRADUAL RULES; FUZZY INPUTS; WELL CONDITIONED SYSTEM.
Ano: 2006 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD200743a00d3f&uri=/notices/prodinra1/2008/02/
Registros recuperados: 5
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