{"id":51896,"date":"2024-08-03T10:28:49","date_gmt":"2024-08-03T02:28:49","guid":{"rendered":"https:\/\/swarma.org\/?p=51896"},"modified":"2024-08-03T10:28:49","modified_gmt":"2024-08-03T02:28:49","slug":"%e6%9e%84%e5%bb%ba%e7%94%9f%e5%91%bd%e7%a7%91%e5%ad%a6%e9%a2%86%e5%9f%9f%e7%9a%84chatgpt%e5%bc%8f%e7%94%9f%e6%88%90%e6%9c%aa%e6%9d%a5%e4%b8%a8%e5%87%a0%e4%bd%95%e6%b7%b1%e5%ba%a6","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=51896","title":{"rendered":"\u6784\u5efa\u751f\u547d\u79d1\u5b66\u9886\u57df\u7684\u201cchatGPT\u201d\u5f0f\u751f\u6210\u672a\u6765\u4e28\u51e0\u4f55\u6df1\u5ea6\u5b66\u4e60\u00b7\u5468\u4e00\u76f4\u64ad"},"content":{"rendered":"
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Proteins are workhorses of living cells. Understanding the functions of proteins is critical to many applications such as biomedicine and synthetic biology. Thanks to recent biotechnology breakthroughs such as gene sequencing and Cro-EM, a large amount of protein data (such as protein sequences and structures) are generated, providing a huge opportunity for AI. As the functions of proteins are determined by their structures, in this talk, I will introduce our recent work on protein understanding based on protein 3D structures with geometric deep learning. I will introduce three different topics including protein representation learning, generative models for protein structure prediction, and generative models for protein design. I will also introduce how these techniques are used for real-world applications in protein design in BioGeometry.<\/span><\/section>\n
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