Identification of transcriptional regulatory variants in pig duodenum, liver, and muscle tissues

Autor: Daniel Crespo-Piazuelo, Hervé Acloque, Olga González-Rodríguez, Mayrone Mongellaz, Marie-José Mercat, Marco C A M Bink, Abe E Huisman, Yuliaxis Ramayo-Caldas, Juan Pablo Sánchez, Maria Ballester

In humans and livestock species, genome-wide association studies (GWAS) have been applied to study the association between variants distributed across the genome and a phenotype of interest. To discover genetic polymorphisms affecting the duodenum, l

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2659::c284f9fd8273c6d9bf486d1c48732139
https://zenodo.org/record/8081207

Imputation to whole-genome sequence and its use in genome-wide association studies for pork colour traits in crossbred and purebred pigs

Autor: Marzieh Heidaritabar, Abe Huisman, Kirill Krivushin, Paul Stothard, Elda Dervishi, Patrick Charagu, Marco C. A. M. Bink, Graham S. Plastow

Publikováno v: Frontiers in Genetics. 13

Imputed whole-genome sequence (WGS) has been proposed to improve genome-wide association studies (GWAS), since all causative mutations responsible for phenotypic variation are expected to be present in the data. This approach was applied on a large n

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a18b940cb3bd5f605ac64c84158fff29
https://doi.org/10.3389/fgene.2022.1022681

Probabilistic Learning in Children With Attention-Deficit/Hyperactivity Disorder

Autor: Marjolein Luman, Tieme W. P. Janssen, Rosa van Mourik, Jaap Oosterlaan, Athanasios Maras, M. Bink

Publikováno v: Journal of Attention Disorders
Luman, M, Janssen, T, Bink, M, van Mourik, R, Maras, A & Oosterlaan, J 2021, ' Probabilistic Learning in Children With Attention-Deficit/Hyperactivity Disorder ', Journal of Attention Disorders, vol. 25, no. 10, pp. 1407-1416 . https://doi.org/10.1177/1087054720905094
Journal of Attention Disorders, 25(10), 1407-1416. SAGE Publications Inc.
Journal of attention disorders. SAGE Publications Inc.

Objective: The current study examined instrumental learning in ADHD. Method: A total of 58 children with ADHD and 58 typically developing (TD) children performed a probabilistic learning task using three reward probability conditions (100%, 85%, 70%

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98abcad9f679787e5e00c739fa26e955
https://doi.org/10.1177/1087054720905094

Prediction performance of linear models and gradient boosting machine on complex phenotypes in outbred mice

Autor: B. C. Perez, Marco C. A. M. Bink, Karen L. Svenson, Gary A. Churchill, Mario P. L. Calus

Publikováno v: G3 (Bethesda, Md.) 12 (2022) 4
G3 (Bethesda, Md.), 12(4)

Recent literature suggests machine learning methods can capture interactions between loci and therefore could outperform linear models when predicting traits with relevant epistatic effects. However, investigating this empirically requires data with

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa2f3339a12ab992db0d7300a843cb46
https://doi.org/10.1093/g3journal/jkac039

Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies

Autor: Laura Rossini, Pere Arús, Thierry Pascal, Ignazio Verde, Sabrina Micali, Igor Pacheco, P. Lambert, Marco C. A. M. Bink, Alessandra Stella, Cassia da Silva Linge, Filippo Biscarini, Bénédicte Quilot-Turion, Daniele Bassi, Nelson Nazzicari, Maria José Aranzana

Publikováno v: Recercat. Dipósit de la Recerca de Catalunya
instname
BMC Genomics 1 (18), . (2017)
BMC Genomics
BMC Genomics, BioMed Central, 2017, 18 (1), ⟨10.1186/s12864-017-3781-8⟩
Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona
BMC genomics 18 (2017): 1–15. doi:10.1186/s12864-017-3781-8
info:cnr-pdr/source/autori:Filippo Biscarini, Nelson Nazzicari1, Marco Bink, Pere Arús, Maria José Aranzana, Ignazio Verde, Sabrina Micali, Thierry Pascal, Benedicte Quilot-Turion6, Patrick Lambert, Cassia da Silva Linge, Igor Pacheco, Daniele Bassi, Alessandra Stella and Laura Rossini/titolo:Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies/doi:10.1186%2Fs12864-017-3781-8/rivista:BMC genomics/anno:2017/pagina_da:1/pagina_a:15/intervallo_pagine:1–15/volume:18
Digital.CSIC: Repositorio Institucional del CSIC
Consejo Superior de Investigaciones Científicas (CSIC)
Recercat: Dipósit de la Recerca de Catalunya
Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
BMC Genomics 18 (2017) 1
BMC Genomics, 18(1)
BMC Genomics, Vol 18, Iss 1, Pp 1-15 (2017)
Digital.CSIC. Repositorio Institucional del CSIC
BMC Genomics, 2017, 18 (1), ⟨10.1186/s12864-017-3781-8⟩
IRTA Pubpro. Open Digital Archive
Institut de Recerca i Tecnologia Agroalimentàries (IRTA)

[Background]: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbb4c28b1f3171fddeb9a2d9811a21e1
http://hdl.handle.net/2072/438838