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2NPLGBM: a genomic model that merges the strengths of classical and machine learning methods in genomic prediction.

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Bibliographic Details
Title: 2NPLGBM: a genomic model that merges the strengths of classical and machine learning methods in genomic prediction.
Authors: Osatohanmwen BE; Division of Plant Breeding Methodology, Department of Crop Sciences, University of Goettingen, 37075, Goettingen, Germany. bright.osatohanmwen@uni-goettingen.de.; Center for Integrated Breeding Research, University of Goettingen, 37075, Goettingen, Germany. bright.osatohanmwen@uni-goettingen.de., Vieira IC; KWS SAAT SE & Co. KGaA, Einbeck, Germany., Sharifi AR; Center for Integrated Breeding Research, University of Goettingen, 37075, Goettingen, Germany.; Division of Animal Breeding and Genetics, Department of Animal Sciences, University of Gottingen, 37075, Goettingen, Germany., Beissinger TM; Division of Plant Breeding Methodology, Department of Crop Sciences, University of Goettingen, 37075, Goettingen, Germany.; Heritable Agriculture, San Carlos, California, 94070, USA.
Source: Plant methods [Plant Methods] 2026 May 28; Vol. 22 (1). Date of Electronic Publication: 2026 May 28.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101245798 Publication Model: Electronic Cited Medium: Print ISSN: 1746-4811 (Print) Linking ISSN: 17464811 NLM ISO Abbreviation: Plant Methods Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1746-4811
DOI:10.1186/s13007-026-01545-2