Compound-Centric Bioremediation Analysis — Local Web Application
BioRemPP Database Explorer is a web application for interactive exploration of the BioRemPP compound-centric database. It is a companion tool to the BioRemPP Web Service and does not require KO annotation files as input — it offers direct browser-based access to compounds, genes, pathways, and toxicity data across all integrated sources.
Built with React + TypeScript (frontend), Express + SQLite (backend), and packaged with Docker + Nginx for deployment.
# 1. Configure environment
cp .env.example .env
# 2. Start production stack (app + Nginx)
docker compose --profile prod up -d --buildOpen: http://localhost:83/bioremppdbx/
For deployment configuration (Nginx, Basic Auth, environment variables), see docs/deployment/docker-compose.md.
npm install
npm run ingest:sqlite
npm run dev:fullOpen: http://localhost:5173/bioremppdbx/
| Module | Entities | Description |
|---|---|---|
| Compounds | Chemical compounds | Search, filter, and inspect per-compound detail |
| Compound Classes | Compound class groups | Aggregate class-level exploration and drill-down |
| Genes / KO | Genes and KO identifiers | Gene–compound connectivity and KO context |
| Pathways | Metabolic pathways | Functional coverage and compound associations per pathway |
| Toxicity | ToxCSM endpoints | 31 toxicity prediction endpoints per compound |
| Databases | Integrated sources | Source schema documentation and field definitions |
Eight curated analytical use cases with reproducible outputs:
| Category | Use Case | Analytical Question |
|---|---|---|
| Compound Analysis | Top Bioremediation Compounds | Which compounds show the broadest functional annotation coverage? |
| Compound Analysis | Most Toxic Compounds | Which compounds present the highest predicted toxicological risk? |
| Compound Analysis | Risk vs Bioremediation Potential | Which compounds combine high degradation potential and high risk? |
| Compound Analysis | Regulated Compounds by Agency | Which compounds are classified by EPA, ATSDR, or IARC? |
| Pathway Analysis | Pathways with Highest Functional Coverage | Which pathways have the highest number of associated KOs? |
| Pathway Analysis | Pathways Associated with Toxic Compounds | Which pathways are linked to compounds with high predicted toxicity? |
| Gene / KO Analysis | Most Connected Genes | Which genes are associated with the largest number of compounds? |
| Gene / KO Analysis | Genes Linked to Toxic Compounds | Which genes are associated with compounds above the selected toxicity threshold? |
| Database | Focus |
|---|---|
| BioRemPP | Core compound-KO-gene mapping for bioremediation |
| KEGG | Xenobiotic metabolism and degradation pathways |
| HADEG | Aerobic hydrocarbon degradation enzymes |
| ToxCSM | Computational toxicity predictions (31 endpoints) |
Regulatory frameworks: IARC, EPA, ATSDR, WFD, PSL, EPC, CONAMA.
Details: Database Schemas
| Section | Description |
|---|---|
| Getting Started | Installation, Docker setup, data ingestion |
| User Guide | Feature walkthrough and results interpretation |
| Guided Analysis | Use case catalog and analytical methodology |
| Database Schemas | Source schemas and field definitions |
| Configuration | Docker Compose profiles, Nginx, environment variables |
| API Reference | TypeScript source reference (TypeDoc) |
When using BioRemPP Database Explorer, please cite both the web service and the database:
Web Service:
Lima Silva, D. F., & Fassarella Agnez-Lima, L. (2026). BioRemPP: A Compound-Centric Web Server for Bioremediation Potential Profiling (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.18919675
Database:
Lima Silva, D. F., & Fassarella Agnez-Lima, L. (2025–2026). BioRemPP Database: A Curated Compound-Centric Resource for Bioremediation Potential Profiling (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18905195
Full citation guidelines: How to Cite
- Source Code: Apache License 2.0
- Database Content: CC BY 4.0
- Third-party: KEGG (academic license), HADEG (open access), ToxCSM (open access)
Details: License
BioRemPP Database Explorer is a research tool for hypothesis generation. Results represent genetic and functional potential, not confirmed biological activity. Not intended for clinical, regulatory, or remediation decisions without experimental validation.
- Documentation: biorempp-dbx.readthedocs.io
- Issues: GitHub Issues
- Email: biorempp@gmail.com
BioRemPP Database Explorer | Documentation | GitHub