Deep learning based secreted protein prediction

Chaoyang Liu; Bo Wang; Xinhong Zhang; Fan Zhang

doi:10.1117/12.3006157

10 October 2023 Deep learning based secreted protein prediction

Chaoyang Liu, Bo Wang, Xinhong Zhang, Fan Zhang

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127991D (2023) https://doi.org/10.1117/12.3006157
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Proteins secreted by various cells and tissues into different body fluids can signal several physiological disorders. However, the degree of complexity in different body fluids and the presence of a large number of proteins in fluids can make studying them with existing proteomics techniques complex and result in large discrepancies between experimental studies. To address this, we developed a deep learning framework called SecBert that identifies secreted proteins in two human body fluids. SecBert uses a sequence-based approach with end-to-end automatic feature extraction for protein classification. Our results show that SecBert performs well, achieving an average area under the ROC curve of 0.94-0.95 on each fluid test dataset.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chaoyang Liu, Bo Wang, Xinhong Zhang, and Fan Zhang "Deep learning based secreted protein prediction", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127991D (10 October 2023); https://doi.org/10.1117/12.3006157

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