Research Unit for Molecular Structure and AI
Aims to integrate structural and functional information of biomolecules such as proteins, peptides, and glycoproteins in a data-centered manner, manage research data from each field, and interpret them using AI-based analytical technologies
Research Content
Conducts research that links protein molecular structure data with large-scale omics data to complement the limitations of conventional experiment-centered research and present new biological insights and predictive models
Research Unit for Molecular Structure and AI
Core Research Fields
Builds core infrastructure for next-generation life science research by elucidating disease mechanisms, discovering drug targets, and identifying uncharacterized proteins through analysis of protein molecular structure data
- Collection of structural data for proteins, peptides, and glycoproteins
- Development of algorithms for research data quality control and automated metadata extraction
- Development of integrated multi-omics analysis algorithms
- Research on AI-based protein function prediction models using molecular structural features
- Prediction of post-translational modification (PTM) sites and their functional impacts
- Research on protein interactions and structural stability analysis
- Development of protein functional annotation and knowledge inference systems
- International standardization activities for protein analysis data
