Multimodal Protein Modeling

Parkinson association may depend on structural, interaction, localization, pathway, and cellular-context factors that sequence-only representations do not fully capture. The findings support integrating complementary biological information beyond primary sequence. Multimodal architectures are presented as a natural next step because disease signals likely emerge across biological levels. Future work should explore task-specific protein language model fine-tuning while maintaining strict validation and leakage control.