A scientific paper analysis tool focused on microbiome research and BugSigDB curation readiness.
- Browse Papers: Search papers by PMID and analyze them for BugSigDB curation readiness
- Chat Assistant: Interactive AI-powered assistance for analysis questions
The system analyzes papers for the following 6 essential fields that determine curation readiness:
- Host Species: Primary organism being studied
- Body Site: Microbiome sample collection location
- Condition: Disease/treatment/exposure being studied
- Sequencing Type: Molecular method used (16S, metagenomics, etc.)
- Taxa Level: Taxonomic level analyzed (phylum, genus, species, etc.)
- Sample Size: Number of samples analyzed
Curation Readiness: A paper is considered ready for curation when all 6 fields are present and well-documented.
- FastAPI Backend: Python-based API server with AI-powered analysis
- AI Models: Integration with Google Gemini for intelligent paper analysis
- Frontend: Modern web interface built with Bootstrap and vanilla JavaScript
- Core Functionality: Automated extraction and assessment of curation fields from scientific papers
- Docker and Docker Compose
- Python 3.11+ (for local development)
- API Keys:
- NCBI API key for PubMed access
- Google Gemini API key for AI analysis
- Clone the repository:
git clone <repository-url>
cd BioAnalyzer
- Create environment file:
cp .env.example .env
# Edit .env with your API keys
- Start the development environment:
./dev.sh start-build
The development environment includes hot reloading:
# Start with build (first time)
./dev.sh start-build
# Start without build (daily development)
./dev.sh start-no-build
# Stop services
./dev.sh stop
# View logs
./dev.sh logs
# Check status
./dev.sh status
POST /enhanced_analysis/{pmid}
Analyze a single paper for BugSigDB curation readiness.
POST /enhanced_analysis_batch
Analyze multiple papers for BugSigDB curation readiness.
GET /curation/statistics
Get statistics about how well the 6 essential curation fields are being identified across all analyzed papers.
Artistic-2.0