PeptideNet: An Integrative Deep Learning Framework for Predicting . . . The integration of large protein language model embeddings with the PeptideNet architecture enables the model to capture both global contextual information and residue-level features, establishing a generalized and interpretable framework for multipeptide bioactivity prediction
通过可解释的深度学习预测蛋白质-肽结合残基 - CSDN博客 文章浏览阅读1 3k次。深度学习预测蛋白质-肽结合位点_predicting protein鈥損eptide binding residues via interpretable deep learning Predicting
PeptideNet: An Integrative Deep Learning Framework for . . . The integration of large protein language model embeddings with the PeptideNet architecture enables the model to capture both global contextual information and residue-level features, establishing a generalized and interpretable framework for multipeptide bioactivity prediction
PeptideNet: An Integrative Deep Learning Framework for Predicting . . . The integration of large protein language model embeddings with the PeptideNet architecture enables the model to capture both global contextual information and residue-level features, establishing a generalized and interpretable framework for multipeptide bioactivity prediction