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来自我们的社区

分享您的专业知识,了解其他科学家和研究人员如何使用 BIOVIA 解决问题。 

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BIOVIA 自学

我们提供丰富的自学模块,以便您能够按照自己的节奏在方便的时间继续进行自学

博客

欢迎阅读 BIOVIA 博客,了解最新消息以及来自我们专家的最新创新。

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Forcefield Optimization for Energetic Materials

Discover how BIOVIA’s computational tools advance the study of molecular crystals, including crystal structure prediction, lattice energy calculations, and the latest COMPASSIII forcefield developments.

Article

Forcefield Optimization for Energetic Materials
Development of Innovative Drugs Using Materials Studio

Discover how BIOVIA Materials Studio, with the Martini 3 force field, enhances lipid nanoparticle and membrane simulations for advanced drug delivery systems. Explore the benefits of molecular dynamics and coarse-grained simulations in optimizing therapeutic formulations.

Article

Development of Innovative Drugs Using Materials Studio
Faster Onboarding with AI Assistants

Discover how integrating large language models enhances onboarding and boosts productivity by offering expert, on-demand assistance for designing and running protocols.

Article

Faster Onboarding with AI Assistants
NMR Crystallography – Solving Organic and Inorganic Structures

NMR crystallography excels in detailing short-range structures in materials using advanced spectrometers and computational tools, with applications in fields like fuel cells and pharmaceuticals, and continues to grow through integrated experimental and computational techniques.

Article

NMR Crystallography – Solving Organic and Inorganic Structures
Empowering Drug Discovery with Machine Learning Workbench

Machine Learning Workbench is a cutting-edge, no-code application designed for data scientists and computational scientists working in the life sciences field. It offers a streamlined, intuitive solution for creating ML models and training pipelines on the 3DEXPERIENCE platform.

Article

Empowering Drug Discovery with Machine Learning Workbench
Learning To Be Narrow

Leveraging BIOVIA for efficient QSAR modeling, showcasing narrow AI’s continued relevance in chemistry amidst general-purpose AI advancements.

Article

Learning To Be Narrow

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