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2. As shown in the figure, the architecture of pLMSNOSite consists of two base models: the supervised embedding layer module and the ProtT5 module, followed by a higher-level meta-model (meta-classifier) that performs the feature-level fusion of base models. We further describe the ...
As shown in the figure, the architecture of pLMSNOSite consists of two base models: the super- vised embedding layer module and the ProtT5 module, followed by a higher-level meta- model (meta-classifier) that performs the feature-level fusion of base models. We further Fig. 2 The ...
We developed pLM4CCPs, a novel deep learning architecture using convolutional neural networks (CNNs) as the classifier for binary classification of CPPs. pLM4CCPs demonstrated superior performance over existing state-of-the-art CPP prediction models, achieving improvements in accuracy (ACC) by 4.9...
Among these, the combination of the SVM classifier and the AADP-PSSM feature set achieved the best prediction accuracy. Second, two popular PLM embeddings, i.e., ESM-2 and ProtT5, were fused with the AADP-PSSM features to further improve the prediction of ATGs. Third, we selected the ...
Among these, the combination of the SVM classifier and the AADP-PSSM feature set achieved the best prediction accuracy. Second, two popular PLM embeddings, i.e., ESM-2 and ProtT5, were fused with the AADP-PSSM features to further improve the prediction of ATGs. Third, we selected the ...