How Can We Help You?

novelBGC is designed for researchers, bioinformaticians, and students working in the fields of microbiology, natural products, and drug discovery. The platform is accessible to users with varying levels of bioinformatics expertise, from beginners to advanced researchers.

Yes, novelBGC is free for academic and non-commercial research purposes. We offer different tiers of service including a free tier with standard features and premium tiers for advanced features and higher computational resources. Please check our pricing page for detailed information.

If you use novelBGC in your research, please cite our publication: [upcoming]. Additionally, please cite the individual tools used in your analysis (e.g., antiSMASH, BiG-SLICE) as they are integral components of our pipeline.

novelBGC is a web application and cannot be installed locally. To use robust pipelines and install similar BGC analysis workflows locally, you may refer to bgcflow, which is designed for local installation and advanced analysis.

novelBGC is built using:
• Backend: Python (Flask), Nextflow for workflow management
• Frontend: HTML5, CSS3, JavaScript, Bootstrap
• Database: PostgreSQL
• Task Queue: Celery with Redis

novelBGC is tested and supported on all major desktop browsers, including Google Chrome, Mozilla Firefox, and Microsoft Edge. Please note that while the site is accessible on mobile browsers, the user experience is not fully optimized for mobile devices and certain features may not display or function correctly.

Analysis time varies depending on:
• Genome size (typically 5-15 minutes for bacterial genomes)
• Server load

You'll receive an email notification when your analysis is complete, and you can monitor progress in the Job Status page.

The novelty score is calculated based on multiple factors:
• Sequence similarity to known BGCs in MIBiG database
• Gene cluster family membership
• Distance to the closest gene cluster family
• Gene cluster family confidence (based on MIBiG presence in GCF)
• Antimicrobial resistance (AMR) gene presence
• Contig edge proximity

The novelty score is calculated using a custom algorithm that combines these factors into a single score. Scores range from 0 (known BGC) to 1 (completely novel).

The results page in novelBGC is divided into four main sections to help you interpret your analysis:

• Summary: Overview of your submission, including job details and key findings.
• Genome Statistics: Information on the quality and features of your input genome, such as total length, N50, and other relevant metrics.
• BGC Distribution: Visualization and summary of all identified Biosynthetic Gene Clusters (BGCs) in your genome, including their types and locations.
• BGC Prioritization: A ranked list of BGCs prioritized based on their novelty scores, providing detailed information for each cluster to help you focus on the most potentially novel or interesting BGCs.

To upload files:
1. Navigate to the Upload page
2. Click "Choose Files" or drag-and-drop your files
3. Give a Genus, Species, and Strain name for your genome
4. Email address (optional) to receive your job ID via email for easy access to results later
5. To tweak weights and thresholds, you can use the Advanced Settings section (Optional)
6. Click "Start Analysis"

Results are stored for 30 days. You can download your results at any time during the storage period. We recommend downloading important results promptly.

Yes! You can download:
• Complete result packages (ZIP archive)
• Individual analysis files
• Interactive HTML reports
• Raw data in various formats (JSON, CSV, TSV)
• Publication-ready figure of the BGC distance to closest GCF distribution

All downloads are available from the Job Status or Results page.

Yes! novelBGC allows you to customize various parameters:
• antiSMASH detection strictness
• Distance to closest GCF thresholds
• Weights for the N/RS score

Advanced users can access these options in the "Advanced Settings" section during upload.

novelBGC integrates several powerful tools:
• antiSMASH: BGC identification
• BiG-SLICE: BGC family clustering
• QUAST: Genome quality assessment
• Prokka: Genome annotation
• Custom algorithms: Novelty scoring, distance calculation
• CARD RGI: Antimicrobial resistance (AMR) gene detection
• MIBiG: BGC similarity search against the MIBiG database
• BIGFAM: BGC family clustering
And more tools are being added regularly!