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Updated: Feb 17, 2026

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化学構造からプラズマにおける無結合分子の構造-性質関係に基づく優れた予測:最小限の記述子を持つ解釈可能なモデル

Indrasis Dasgupta1, Samima Khatun1, Shovanlal Gayen1

  • 1Laboratory of Drug Design and Discovery, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.

Molecular informatics
|February 15, 2026
PubMed
まとめ

プラズマの未結合分数 (fup) を予測することは,薬剤発見において極めて重要です. 私たちの読み越しの定量的な構造-性質関係モデルは,合理的な薬剤設計を支援し,改善された,解釈可能な予測を提供します.

キーワード:
ドラッグ・バインド・ドラッグ・バインド分類と回帰による分類血に結合されていない分子は,機械学習 (Machine Learning) とは,機械学習 (Machine Learning) とは,機械学習 (Machine Learning) と呼ばれるものです.read-across 構造 財産関係の構造 財産関係の構造 財産関係の構造

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