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| title: PhytoAI Assistant | |
| emoji: 🌿 | |
| colorFrom: green | |
| colorTo: blue | |
| sdk: streamlit | |
| sdk_version: 1.28.0 | |
| app_file: app.py | |
| pinned: false | |
| license: cc-by-4.0 | |
| tags: | |
| - phytotherapy | |
| - natural-compounds | |
| - bioactivity | |
| - drug-discovery | |
| - ai-assistant | |
| - research-tool | |
| # PhytoAI Assistant 🌿 | |
| **Interactive AI Assistant for Phytotherapy Research** - Explore natural compounds and their bioactivities using cutting-edge AI technology. | |
| ## 🎯 Overview | |
| The PhytoAI Assistant is an interactive web application built with Streamlit that provides researchers, students, and pharmaceutical professionals with easy access to a comprehensive database of natural compounds and their documented bioactivities. This tool leverages the [PhytoAI MEGA Dataset](https://huggingface.co/datasets/Gatescrispy/phytoai-mega-dataset) containing 352 unique natural compounds and 1,314 bioactivities. | |
| ## ✨ Key Features | |
| ### 🔍 Advanced Search Capabilities | |
| - **Compound Name Search**: Find specific natural compounds by name (e.g., curcumin, resveratrol, quercetin) | |
| - **Therapeutic Activity Search**: Discover compounds by their therapeutic properties: | |
| - Anti-inflammatory | |
| - Antioxidant | |
| - Cardiovascular protective | |
| - Neuroprotective | |
| - Anti-cancer | |
| - Antimicrobial | |
| ### 📊 Interactive Data Visualization | |
| - **Real-time Statistics**: Live metrics on compound count, bioactivities, and therapeutic coverage | |
| - **Distribution Charts**: Visual analysis of therapeutic activities using Plotly | |
| - **Pie Charts**: Therapeutic area distribution for quick insights | |
| - **Bar Charts**: Activity type frequency analysis | |
| ### 🧬 Comprehensive Compound Information | |
| - **Molecular Properties**: Chemical formulas, SMILES notation, molecular weights | |
| - **Database Cross-references**: PubChem CID mappings for further research | |
| - **Bioactivity Profiles**: Detailed activity descriptions with experimental context | |
| - **Literature References**: Links to original research and validation studies | |
| ## 🚀 How to Use | |
| 1. **Launch the Application**: The interface loads automatically with dataset statistics | |
| 2. **Search Compounds**: Use the sidebar to search by compound name or therapeutic activity | |
| 3. **Explore Results**: Click on compound cards to see detailed molecular and bioactivity information | |
| 4. **Analyze Data**: Review interactive charts to understand therapeutic distribution patterns | |
| 5. **Cross-reference**: Use PubChem CIDs for additional research in external databases | |
| ## 📈 Dataset Integration | |
| This application seamlessly integrates with the **PhytoAI MEGA Dataset** through Hugging Face's `hf_hub_download` functionality, ensuring: | |
| - **Always Up-to-date**: Automatic synchronization with the latest dataset version | |
| - **Efficient Loading**: Cached data loading for optimal performance | |
| - **Reliable Access**: Robust error handling and fallback mechanisms | |
| ## 🔬 Research Applications | |
| ### Academic Research | |
| - **Drug Discovery**: Identify promising natural compounds for pharmaceutical development | |
| - **Ethnopharmacology**: Validate traditional medicine uses with modern bioactivity data | |
| - **Chemical Biology**: Explore structure-activity relationships in natural products | |
| ### Pharmaceutical Industry | |
| - **Lead Compound Identification**: Screen natural products for specific therapeutic targets | |
| - **Bioactivity Prediction**: Use existing data to guide synthetic chemistry efforts | |
| - **Competitive Intelligence**: Monitor natural product research trends and opportunities | |
| ### Educational Use | |
| - **Teaching Tool**: Interactive exploration of phytochemistry and pharmacology concepts | |
| - **Student Projects**: Real-world dataset for bioinformatics and cheminformatics training | |
| - **Research Training**: Hands-on experience with pharmaceutical data analysis | |
| ## 🛠️ Technical Architecture | |
| ### Frontend | |
| - **Streamlit**: Modern, responsive web interface | |
| - **Plotly**: Interactive data visualizations | |
| - **Pandas**: Efficient data manipulation and analysis | |
| ### Backend | |
| - **Hugging Face Hub**: Dataset storage and version control | |
| - **JSON/CSV**: Structured data formats optimized for research | |
| - **Caching**: Optimized performance with Streamlit's caching system | |
| ### Data Pipeline | |
| ```Hugging Face Dataset → hf_hub_download → JSON Loading → | |
| Pandas Processing → Streamlit Interface → Interactive Visualizations | |
| ``` | |
| ## 📊 Dataset Statistics | |
| - **🧬 Compounds**: 352 unique natural products | |
| - **🔬 Bioactivities**: 1,314 documented activities | |
| - **🎯 Therapeutic Areas**: 6+ major categories | |
| - **📚 Sources**: PubChem, ChEMBL, peer-reviewed literature | |
| - **🔄 Updates**: Regularly maintained and expanded | |
| ## 🌐 Related Resources | |
| - **📊 Dataset**: [PhytoAI MEGA Dataset](https://huggingface.co/datasets/Gatescrispy/phytoai-mega-dataset) | |
| - **🤖 Models**: [PhytoAI Discovery Models](https://huggingface.co/Gatescrispy/phytoai-discovery-models) | |
| - **📖 Documentation**: Comprehensive API and usage documentation | |
| - **💬 Community**: Research collaboration and support forum | |
| ## 🏆 Impact & Recognition | |
| This tool has been designed to bridge the gap between traditional phytotherapy knowledge and modern AI-driven drug discovery, providing researchers worldwide with: | |
| - **Accessible Data**: User-friendly interface for complex bioactivity data | |
| - **Research Acceleration**: Rapid compound screening and hypothesis generation | |
| - **Global Collaboration**: Shared platform for international research initiatives | |
| - **Educational Value**: Training resource for next-generation researchers | |
| ## 📄 Citation & License | |
| **License**: CC BY 4.0 - Free for academic and commercial use with attribution | |
| **Citation**: If you use PhytoAI Assistant in your research, please cite: | |
| ```bibtex | |
| @software{phytoai_assistant_2025, | |
| title={PhytoAI Assistant: Interactive AI Tool for Phytotherapy Research}, | |
| author={Tantcheu, Cedric}, | |
| year={2025}, | |
| url={https://huggingface.co/spaces/Gatescrispy/phytoai-assistant}, | |
| note={Interactive Streamlit application for natural compound bioactivity exploration} | |
| } | |
| ``` | |
| ## 👨💻 About the Developer | |
| **Cedric Tantcheu** - AI & Phytotherapy Research Specialist | |
| - 🎓 Expertise in cheminformatics, machine learning, and natural product research | |
| - 🔬 Focus on AI-driven drug discovery from traditional medicine | |
| - 🌍 Committed to open science and global health solutions | |
| --- | |
| **🌿 Advancing phytotherapy research through intelligent technology** | |
| *Built with ❤️ for the global research community* | |