Inspiration
What it does
How we built it
Challenges we ran into
About the Project – BioInsight AI 2.0
Inspiration
We were inspired to simplify biological research by addressing the challenges researchers face when using multiple scientific databases and tools for molecular analysis and drug discovery. We wanted to bring these capabilities together into one accessible platform.
What We Learned
During development, we gained practical experience in AI-powered applications, bioinformatics, scientific database integration, molecular docking, 3D visualization, API development, and full-stack engineering. We also learned the importance of scientific accuracy, data attribution, and secure software development.
How We Built It
We developed BioInsight AI 2.0 using a Next.js frontend and FastAPI backend, integrated with PostgreSQL and 11 scientific database connectors. We incorporated AutoDock Vina 1.2.5 for molecular docking, interactive 3D molecular visualization, background job processing, and automated research report generation.
Challenges We Faced
Our major challenges included integrating multiple scientific databases, handling different biological data formats, managing computational docking workflows, ensuring reliable background job execution, and maintaining secure data handling. We addressed these challenges through modular development, error handling, testing, and systematic verification.
Our Vision
Our vision is to make bioinformatics research more accessible, efficient, and organized by providing researchers and students with a unified platform for exploring biological data and supporting early-stage computational drug discovery.
Accomplishments that we're proud of
What we learned
What's next for BioInsight AI 2.0
Built With
- biobase
- bioinformatics
- drug-discovery
- machine-learning
- national-drug-file-reference-terminology
- python
