835eca38fa3bb01bedb8ff869c2a0d37 froplasci_a2020m2v11p25.pdf 63539a03a7e5d239fee1f776b17e419e245ef799 froplasci_a2020m2v11p25.pdf e8379ec67edaac567159fd19d3586342f112e76707fd772c9428bb8250b0062a froplasci_a2020m2v11p25.pdf Title: Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species Subject: Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates are predicted using genome wide marker information Keywords: genomic prediction, genomic selection, polyploid species, deep learning, epistasis, complex traits, strawberry, blueberry Author: Laura M. 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Zingaretti Salvador Alejandro Gezan Luis Felipe V. Ferrão Luis F. Osorio Amparo Monfort Patricio R. Muñoz Vance M. Whitaker Miguel Pérez-Enciso Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates are predicted using genome wide marker information Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species genomic prediction genomic selection polyploid species deep learning epistasis complex traits strawberry blueberry 2020-02-05T09:05:14+08:00 Arbortext Advanced Print Publisher 10.0.1306/W Unicode 2020-07-31T17:09:13+02:00 2020-07-31T17:09:13+02:00 Acrobat Distiller 10.0.0 (Windows) genomic prediction, genomic selection, polyploid species, deep learning, epistasis, complex traits, strawberry, blueberry uuid:91d83f2b-f00a-4cc1-8ae4-a2acf036cc11 uuid:84bd6af8-3fb2-4982-8aac-627280233054 Pages: Page: Label: 1 Annotations: Annotation: Subtype: Link Rect: 175, 607, 549, 628 Annotation: Subtype: Link Rect: 175, 584, 545, 605 Annotation: Subtype: Link Rect: 175, 561, 381, 582 Annotation: Subtype: Link Rect: 175, 538, 215, 547 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