A graph neural network approach for hierarchical mapping of breast cancer protein communities.
Journal:
BMC bioinformatics
PMID:
39838298
Abstract
BACKGROUND: Comprehensively mapping the hierarchical structure of breast cancer protein communities and identifying potential biomarkers from them is a promising way for breast cancer research. Existing approaches are subjective and fail to take information from protein sequences into consideration. Deep learning can automatically learn features from protein sequences and protein-protein interactions for hierarchical clustering.