pLMFPPred: a novel approach for accurate prediction of functional peptides integrating embedding from pre-trained protein language model and imbalanced learning

1 code implementation • 25 Sep 2023 • Zebin Ma, Yonglin Zou, Xiaobin Huang, Wenjin Yan, Hao Xu, Jiexin Yang, Ying Zhang, Jinqi Huang

Comparative experiments show that pLMFPPred outperforms current methods for predicting functional peptides. The experimental results suggest that the proposed method (pLMFPPred) can provide better performance in terms of Accuracy, Area under the curve - Receiver Operating Characteristics, and F1-Score than existing methods.

feature selection Protein Language Model