Data Engineering
Curating datasets and modeling allosteric dynamics with precision.
Dynamic GNN
Modeling distance fluctuations and residue attention layers.
Physics-Aware
Incorporating energy terms and spectroscopy constraints for validation.
Advanced Data Engineering
Specializing in allosteric datasets, spatiotemporal graphs, and dynamic GNN model development.
Dynamic Graph Neural Networks
Utilizing edge weights and attention layers for enhanced residue-level analysis in models.
Physics-Aware Training
Incorporating energy terms and spectroscopy constraints into loss functions for improved accuracy.
Validation Techniques
Verifying dynamics and testing allosteric switches in synthetic biology applications effectively.
Innovative Data Engineering Solutions
Specializing in allosteric dataset curation and advanced modeling techniques for structural biology applications.