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Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses

Research article (Theoretical and Applied Genetics, 2021) · cited 15× · AI/ML
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Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses

Summary

Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses is a scholarly article[1].

Key Facts

  • Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses. Retrieved May 24, 2026, from https://4ort.xyz/entity/genomic-prediction-models-trained-with-historical-records-enable-populating-the-german-ex-situ-genebank-bio-digital-reso
MLA “Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/genomic-prediction-models-trained-with-historical-records-enable-populating-the-german-ex-situ-genebank-bio-digital-reso.
BibTeX @misc{4ortxyz_genomic-prediction-models-trained-with-historical-records-enable-populating-the-german-ex-situ-genebank-bio-digital-reso_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses}}, year = {2026}, url = {https://4ort.xyz/entity/genomic-prediction-models-trained-with-historical-records-enable-populating-the-german-ex-situ-genebank-bio-digital-reso}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses — https://4ort.xyz/entity/genomic-prediction-models-trained-with-historical-records-enable-populating-the-german-ex-situ-genebank-bio-digital-reso (retrieved 2026-05-24)

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