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

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

q-bio.QM2023★ 2 cited

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

Zebin Ma, Yonglin Zou, Xiaobin Huang +5

Functional peptides have the potential to treat a variety of diseases. Their good therapeutic efficacy and low toxicity make them ideal therapeutic agents. Artificial intelligence-…

cs.CV2023

Semi-Supervised Learning with Pseudo-Negative Labels for Image Classification

Hao Xu, Hui Xiao, Huazheng Hao +3

Semi-supervised learning frameworks usually adopt mutual learning approaches with multiple submodels to learn from different perspectives. To avoid transferring erroneous pseudo la…