Spectra Comparison
AI Model Architecture
Prediction Accuracy
Overview
Our AI-powered system can accurately predict MS spectra from chemical structures, revolutionizing the way we approach chemical analysis.
The Challenge
Traditional methods of obtaining MS spectra require physical samples and time-consuming laboratory analysis. We aimed to create a predictive system that could generate accurate spectra from structural information alone.
Our Solution
We developed a deep learning model that can:
- Generate MS spectra from chemical structures
- Predict fragmentation patterns
- Estimate relative peak intensities
- Account for different ionization methods
Technical Details
The system uses a combination of graph neural networks and transformer architectures to learn the relationship between chemical structures and their corresponding mass spectra. The model has been trained on a comprehensive database of experimental spectra.