Ferroptosis is a distinct iron-dependent form of regulated cell death that plays critical roles in cancer progression, neurodegenerative disorders, and immune regulation. Computational identification of ferroptosis-related proteins (FRPs) remains challenging due to the complex regulatory network of ferroptosis, the functional heterogeneity of FRPs, and the limited availability of experimentally validated data. Accurate and high-throughput prediction of FRPs is therefore urgently needed. To addre
Contrastive representation learning and capsule networks enable accurate identification of ferroptosis-related proteins
Yiyang Zhao·Lantian Yao·Peilin Xie·Jiahui Guan·Zhihao Zhao·Junwen Wang·Tzong-Yi Lee·Ying-Chih Chiang·Leyi Wei·Xiangrong Liu·Xingchen Liu
