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Updated: Sep 10, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

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ACLPred:説明可能な機械学習と抗癌リガンド予測のためのツリーベースのアンサンブルモデル

Arvind Kumar Yadav1, Jun-Mo Kim2

  • 1Functional Genomics & Bioinformatics Laboratory, Department of Animal Science and Technology, Chung-Ang University, Anseong, 17546, Gyeonggi-do, Republic of Korea.

Scientific reports
|August 25, 2025
PubMed
まとめ

機械学習 (ML) は,分子特性を分析することによって,新しい抗癌薬の発見を加速します. 新しいツールであるACLPredは,Light Gradient Boosting Machine (LGBM) を使用して,潜在的な抗がん化合物を正確に予測し,時間とリソースを節約します.

キーワード:
抗癌リガンド癌について機械学習を統合するマルチステップ機能の選択

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