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Updated: Sep 10, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

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統合されたゲノム予測と機械学習のGWASワークフローにおける大豆のGxE効果を解明する

Niel Verbrigghe1, Hilde Muylle2, Marie Pegard3

  • 1Plant Sciences Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Melle, Belgium. niel.verbrigghe@ilvo.vlaanderen.be.

Plant methods
|August 26, 2025
PubMed
まとめ

ゲノムによる環境 (GxE) 相互作用を統合することでゲノム予測モデルが改善された. ゲノム予測と機械学習-全ゲノム関連研究 (ML-GWAS) を組み合わせた新しいアプローチは,予測能力を高め,大豆の重要な遺伝子マーカーを特定します.

キーワード:
GWAS についてゲノム予測GxE について機械学習ランダムな森林大豆

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