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Updated: Jan 8, 2026

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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生物信息算法在现代生物制药设计中的作用:进展,挑战和未来的前景

Mohammad Mostafa Pourseif1,2,3,4, Seyed Ali Baradaran Hosseini1,5, Seyed Hossein Khoshraftar1,6

  • 1Research Center for Pharmaceutical Nanotechnology, Biomedicine Institute, Tabriz University of Medical Sciences, Tabriz, Iran.

BioImpacts : BI
|December 18, 2025
PubMed
概括

人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 正通过加速蛋白质结构和功能预测来改变药物发现. 这些先进的生物信息学方法简化了生物制药开发,尽管数据和可解释性仍然存在挑战.

关键词:
由人工智能驱动的生物制药.药物设计 药物设计在的生物制药.机器学习是机器学习.预测算法 预测算法结构生物信息学 结构生物信息学系统生物学 系统生物学

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