Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations
收藏NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/10628224
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This dataset encompasses and describes the following features:
Mutations in viruses like SARS-CoV-2 can make them escape vaccines and treatments.
Accurately predicting these mutations is crucial for developing effective countermeasures.
The study uses a type of AI called a Generative Adversarial Network (GAN) to analyze the virus's spike protein, which plays a key role in infection.
The GAN generates protein sequences similar to natural ones, but which are also likely to evade immune responses.
By analyzing these generated sequences, the researchers improve their AI model's ability to predict real-world escape mutations.
This improved prediction could help design better vaccines and treatments, and prepare for future viral threats.
创建时间:
2024-07-02



