Proteomics
Advanced computational tools for protein analysis, structure prediction, and biomarker discovery
Our Tools
ProteomeDiscoverer AI
AI-enhanced protein identification and quantification
Structure Predictor
Deep learning-based protein structure prediction
BiomarkerMiner
Automated biomarker discovery and validation
MassSpecAnalyzer
Advanced mass spectrometry data processing
Technology Stack
- TensorFlow and PyTorch
- AlphaFold 2
- Biopython
- Scikit-learn
- Apache Spark
- PostgreSQL
- Docker and Kubernetes
- React and TypeScript
Public Databases We Integrate
Case Study: Cancer Biomarker Discovery in Clinical Trials
Challenge
A leading pharmaceutical company needed to identify novel protein biomarkers for early-stage cancer detection from thousands of patient samples. Traditional manual analysis would take months and risk missing subtle patterns.
Solution
We deployed our ProteomeDiscoverer AI and BiomarkerMiner tools to analyze mass spectrometry data from 5,000+ patient samples. Our AI models processed protein expression profiles, identified differential patterns, and validated candidate biomarkers against UniProt and PRIDE databases.
Results
- 85% reduction in analysis time (from 6 months to 3 weeks)
- 12 novel biomarkers identified with 92% sensitivity and 89% specificity
- 3 biomarkers advanced to Phase II clinical trials
- $2.4M saved in research and development costs