Create README

README

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+# 🧬 CANLoc — Protein Subcellular Localization Predictor
+
+CANLoc is a machine learning web application for predicting the subcellular localization of proteins directly from protein sequences.  
+It provides accurate, fast, and interpretable predictions through a modern deep-learning–assisted pipeline and an interactive web interface.
+
+---
+
+## 🔬 Model Overview
+
+CANLoc combines:
+
+- **ESM2 (Transformer-based protein language model)**  
+  Used for extracting rich sequence embeddings without alignment.
+
+- **Mean pooling of residue embeddings**  
+  Produces fixed-length feature vectors.
+
+- **XGBoost classifier**  
+  Trained on curated protein datasets for robust multiclass prediction.
+
+### Predicted Classes
+- Cytoplasm  
+- Nucleus  
+- Membrane  
+- Mitochondria  
+
+Each prediction includes **class probabilities** and **confidence visualization.**
+
+---
+
+## 📊 Features
+
+- Single sequence prediction
+- Batch prediction via FASTA file upload
+- Probability bar chart and radar plot
+- Confidence-based interpretation
+- Clean, responsive bioinformatics-style UI
+- Dockerized for reproducible deployment
+- FastAPI backend + modern frontend
+
+---
+
+## 🧪 Input Formats
+
+### Single Sequence
+Paste a raw amino acid sequence: MVKFKKYGIP...
+
+
+### FASTA File
+Upload a standard FASTA file with one or multiple sequences:
+sp|P25296|CANB_YEAST
+MSLIHPDTAKYPFKFEPF...
+
+
+---
+
+## 📈 Output Interpretation
+
+- **Predicted Location**  
+  The most probable subcellular class.
+
+- **Class Probabilities**  
+  Displayed as percentages for all four classes.
+
+- **Confidence Levels**
+  - High: ≥ 75%
+  - Medium: 60–75%
+  - Low: < 60% (interpret with caution)
+
+---
+
+## ⚙️ Evaluation & Validation
+
+The model was evaluated using:
+- Train/test split
+- 10-fold stratified cross-validation
+- Precision, recall, F1-score
+- Sensitivity and specificity analysis
+- ROC curves per class
+
+These evaluations confirm CANLoc’s reliability for academic/research workflows..
+
+
+---
+
+## 🚀 Deployment
+
+CANLoc is containerized and deployed using **Docker**.
+
+## 📄 License
+This project is licensed under the Apache License 2.0.
+
+>Free for academic and commercial use
+>Includes patent protection
+>No restrictions on deployment or modification
+
+See the LICENSE file for details.
+
+
+## 📬 Contact
+
+For questions, bug report or feedback:
+majidkhan>jssmsc@gmail.com
+
+## 📌 Citation
+
+If you use CANLoc in academic work, please cite appropriately.