S2ALM:シーケンスの構造を備えた,包括的な抗体表現学習のための,事前に訓練された大型言語モデル

Mingze Yin1,2, Hanjing Zhou3, Jialu Wu4

  • 1College of Computer Science and Technology, Zhejiang University, Hangzhou, China.

PubMed
まとめ

新しいシーケンス・ストラクチャー・マルチレベル・プレトレーニング・アンチボディ・ランゲージ・モデル (S2ALM) は,抗体のシーケンスと構造を統合して,治療開発を改善します. この高度なモデルは様々な病気に対する 抗体の理解と設計を向上させます

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