Model fusion for predicting unconventional proteins secreted by exosomes using deep learning

In this study, we propose a novel approach to predict UPSEs by combining multiple deep learning models that incorporate both protein sequences and evolutionary information. Our approach utilizes a convolutional neural network (CNN) to extract protein sequence information, while various densely connected neural networks (DNNs) are employed to capture evolutionary conservation patterns.By combining six distinct deep learning models, we have created a superior framework that surpasses previous approaches, achieving an ACC score of 77.46% and an MCC score of 0.5406 on an independent test dataset.

Source: Proteomics - April 21, 2024 Category: Biochemistry Authors: Yonglin Zhang, Lezheng Yu, Ming Yang, Bin Han, Jiesi Luo, Runyu Jing Tags: RESEARCH ARTICLE Source Type: research