BioinfoXpert Launches ACP-Finder: Browser-Based Anticancer Peptide Prediction
We're excited to announce the launch of ACP-Finder (ACPF), our innovative web application for predicting the anticancer potential of peptide sequences! This tool brings advanced machine learning capabilities directly to your browser, eliminating the need for Python installations or server-side processing.
What's New
ACP-Finder offers:
- Machine Learning Predictions: Uses a Random Forest Classifier trained on extensive datasets for 89% accuracy
- Browser-Based Processing: All computations happen client-side; your data never leaves your device
- Multiple Input Formats: Support for FASTA files or direct sequence input
- Feature Highlighting: Visual insights into key peptide characteristics
- 3D Structure Preview: Optional integration with ESMFold for molecular visualization
Key Features
- High Accuracy: 89% prediction accuracy based on balanced training datasets
- User-Friendly Interface: Intuitive Streamlit-based design accessible to all researchers
- Comprehensive Analysis: Includes probability scores, class labels, and feature importance
- Privacy-Focused: No data transmission required; everything runs locally
- Open Access: Free to use for academic and research purposes
How It Works
Simply input your peptide sequences or upload FASTA files. ACP-Finder processes them using our trained model to provide:
- Probability scores for anticancer potential
- Binary classification (anticancer/non-anticancer)
- Feature importance rankings
- Optional 3D structure visualization for positive predictions
Why Choose ACP-Finder?
Developed by our team of bioinformatics experts, ACP-Finder represents the future of accessible peptide research tools. Whether you're in drug discovery, peptide engineering, or basic research, this tool provides rapid, reliable predictions to accelerate your work.
Get Started
Ready to predict anticancer peptides? Visit our tools page and launch ACP-Finder today!
Try ACP-Finder now or learn more about our tools.