Multi-scale deep learning for the imbalanced multi-label protein subcellular localization prediction based on immunohistochemistry images.
Journal:
Bioinformatics (Oxford, England)
PMID:
35212728
Abstract
MOTIVATION: The development of microscopic imaging techniques enables us to study protein subcellular locations from the tissue level down to the cell level, contributing to the rapid development of image-based protein subcellular location prediction approaches. However, existing methods suffer from intrinsic limitations, such as poor feature representation ability, data imbalanced issue, and multi-label classification problem, greatly impacting the model performance and generalization.