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14 p, 2.1 MB |
kernInt : A Kernel Framework for Integrating Supervised and Unsupervised Analyses in Spatio-Temporal Metagenomic Datasets
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Ramon, Elies (Centre de Recerca en Agrigenòmica) ;
Belanche-Muñoz, Lluís (Universitat Politècnica de Catalunya. Departament d'Informàtica) ;
Molist, Francesc (Schothorst Feed Research) ;
Quintanilla, Raquel (Institut de Recerca i Tecnologia Agroalimentàries) ;
Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica) ;
Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries)
The advent of next-generation sequencing technologies allowed relative quantification of microbiome communities and their spatial and temporal variation. In recent years, supervised learning (i. e. , prediction of a phenotype of interest) from taxonomic abundances has become increasingly common in the microbiome field. [...]
2021 -  10.3389/fmicb.2021.609048
Frontiers in microbiology, Vol. 12 (January 2021) , art. 609048
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11 p, 1.4 MB |
Whole-genome sequencing reveals insights into the adaptation of French Charolais cattle to Cuban tropical conditions
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Ramírez-Ayala, Lino César (Centre de Recerca en Agrigenòmica) ;
Rocha, Dominique (Institut national de la recherche agronomique. Génétique Animale et Biologie Intégrative) ;
Ramos-Onsins, Sebastian (Centre de Recerca en Agrigenòmica) ;
Leno Colorado, Jordi (Centre de Recerca en Agrigenòmica) ;
Charles, Mathieu (Institut national de la recherche agronomique. Génétique Animale et Biologie Intégrative) ;
Bouchez, Olivier (Institut National de la Recherche Agronomique (França)) ;
Rodríguez Valera, Yoel (Universidad de Granma. Facultad de Ciencias Agropecuarias) ;
Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica) ;
Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries)
In the early 20th century, Cuban farmers imported Charolais cattle (CHFR) directly from France. These animals are now known as Chacuba (CHCU) and have become adapted to the rough environmental tropical conditions in Cuba. [...]
2021 - 10.1186/s12711-020-00597-9
Genetics, selection, evolution, Vol. 53 (2021)
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14 p, 1.9 MB |
Exploring deep learning for complex trait genomic prediction in polyploid outcrossing species
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Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ;
Gezan, Salvador Alejandro (University of Florida. School of Forest Resources and Conservation (USA)) ;
Ferrão, Luis Felipe V. (University of Florida. Horticultural Sciences Department (USA)) ;
Osorio, Luis F. (University of Florida. IFAS Gulf Coast Research and Education Center (USA)) ;
Monfort Vives, Amparo (Centre de Recerca en Agrigenòmica) ;
Muñoz, Patricio R. (University of Florida. Horticultural Sciences Department (USA)) ;
Whitaker, Vance M. (University of Florida. IFAS Gulf Coast Research and Education Center (USA)) ;
Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica)
Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates are predicted using genome wide marker information. Although numerous examples of GP exist in plants and animals, applications to polyploid organisms are still scarce, partly due to limited genome resources and the complexity of this system. [...]
2020 - 10.3389/fpls.2020.00025
Frontiers in plant science, Vol. 11 (February 2020) , art. 25
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3 p, 575.2 KB |
Aplicacions de l''aprenentatge profund' (Deep Learning) per a la millora genètica dels poliploides
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Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica)
Un article recentment publicat per autors del Centre de Recerca en Agrigenòmica (CRAG) i de la Universitat de Florida mostra com els mètodes computacionals moderns poden ajudar en la millora genètica d'espècies vegetals amb més de dos jocs de cromosomes.
Un artículo recientemente publicado por autores del Centre de Recerca en Agrigenòmica (CRAG) y de la Universidad de Florida muestra cómo los métodos computacionales modernos pueden ayudar en el mejoramiento genético de las especies vegetales con más de dos juegos de cromosomas.
An article recently published by CRAG (Centre de Recerca en Agrigenòmica) and researchers of the University of Florida shows how modern computational methods can help in the genetic improvement of plant species with more than two sets of chromosomes.
2020
UAB divulga, Juliol 2020
3 documents
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11 p, 594.5 KB |
Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows
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Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries. Torre Marimon) ;
Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica) ;
Popova, Milka (Université Clermont Auvergne. Institut National de la Recherche Agronomique. VetAgro Sup (France)) ;
Estellé Fabrellas, Jordi (Université Paris-Saclay. Institut National de la Recherche Agronomique. Génétique Animale et Biologie Intégrative (France)) ;
Bernard, Aurelien (Université Clermont Auvergne. Institut National de la Recherche Agronomique. VetAgro Sup (France)) ;
Pons, Nicolas (Institut National de la Recherche Agronomique. Metagenopolis Unit (France)) ;
Bellot, Pau (Centre de Recerca en Agrigenòmica) ;
Mach, Núria (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France)) ;
Rau, Andrea (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France)) ;
Roume, Hugo (Institut National de la Recherche Agronomique. Metagenopolis Unit (France)) ;
Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica) ;
Faverdin, Philippe (Institut National de la Recherche Agronomique (França)) ;
Edouard, Nadège (Institut National de la Recherche Agronomique (França)) ;
Ehrlich, Dusko (Institut National de la Recherche Agronomique. Metagenopolis Unit (France)) ;
Morgavi, Diego P. (Université Clermont Auvergne. Institut National de la Recherche Agronomique (France)) ;
Renand, Gilles (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France))
Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. [...]
2020 - 10.1111/jbg.12427
Journal of Animal Breeding and Genetics, Vol. 137, Issue 1 (January 2020) , p. 49-59
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16 p, 1.0 MB |
Characterization of the porcine nutrient and taste receptor gene repertoire in domestic and wild populations across the globe
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da Silva, Elizabete C. (Centre de Recerca en Agrigenòmica) ;
de Jager, Nadia (University of Queensland. Centre for Nutrition and Food Sciences.) ;
Burgos-Paz, William (Centre de Recerca en Agrigenòmica) ;
Reverter, Antonio (CSIRO. Agriculture and Food) ;
Roura, Eugeni (University of Queensland. Centre for Nutrition and Food Sciences) ;
Perez-Enciso, Miguel (Universitat Autònoma de Barcelona. Departament de Ciència Animal i dels Aliments)
The oral GPCR nutrient/taste receptor gene repertoire consists of the Tas1r family (sweet and umami tastes), the Tas2r family (bitter taste) as well as several other potential candidate sensors of amino acids, peptones and fatty acids. [...]
2014 - 10.1186/1471-2164-15-1057
BMC genomics, Vol. 15 (2014)
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