View in EDS

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

Saved in:
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
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 42210373
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: 2NPLGBM: a genomic model that merges the strengths of classical and machine learning methods in genomic prediction.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Osatohanmwen+BE%22">Osatohanmwen BE</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Vieira+IC%22">Vieira IC</searchLink>; KWS SAAT SE & Co. KGaA, Einbeck, Germany.<br /><searchLink fieldCode="AU" term="%22Sharifi+AR%22">Sharifi AR</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Beissinger+TM%22">Beissinger TM</searchLink>; Division of Plant Breeding Methodology, Department of Crop Sciences, University of Goettingen, 37075, Goettingen, Germany.; Heritable Agriculture, San Carlos, California, 94070, USA.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101245798%22">Plant methods</searchLink> [Plant Methods] 2026 May 28; Vol. 22 (1). <i>Date of Electronic Publication: </i>2026 May 28.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22BioMed+Central%22">BioMed Central </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101245798 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Print <i>ISSN: </i>1746-4811 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2217464811%22">17464811 </searchLink><i>NLM ISO Abbreviation: </i>Plant Methods <i>Subsets: </i>PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=42210373
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1186/s13007-026-01545-2
    Languages:
      – Code: eng
        Text: English
    Titles:
      – TitleFull: 2NPLGBM: a genomic model that merges the strengths of classical and machine learning methods in genomic prediction.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Osatohanmwen BE
      – PersonEntity:
          Name:
            NameFull: Vieira IC
      – PersonEntity:
          Name:
            NameFull: Sharifi AR
      – PersonEntity:
          Name:
            NameFull: Beissinger TM
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 28
              M: 05
              Text: 2026 May 28
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 1746-4811
          Numbering:
            – Type: volume
              Value: 22
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Plant methods
              Type: main
ResultId 1