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Single-sequence protein structure prediction using supervised transformer protein language models
Single-sequence protein structure prediction using supervised transformer protein language models
组织者
演讲者
石想
时间
2024年09月09日 15:00 至 15:30
地点
理科楼A-304 ；腾讯会议号409-8700-4974
摘要
The authors introduce trRosettaX-Single, an automated algorithm for single-sequence protein structure prediction. It incorporates the sequence embedding from a supervised transformer protein language model into a multi-scale network enhanced by knowledge distillation to predict inter-residue two-dimensional geometry, which is then used to reconstruct three-dimensional structures via energy minimization.