Genome Hub

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Inspiration

The inspiration behind Genome Hub lies in the challenge of navigating vast and scattered NASA bioscience publications related to human and biological spaceflight experiments. The project aims to simplify access to decades of research, supporting the next era of human space exploration by enabling scientists and mission planners to quickly discover impactful insights from complex biological data generated in space environments.

What it does

Genome Hub is an AI-powered interactive dashboard that organizes, summarizes, and visualizes over 600 NASA bioscience publications. It enables users to explore experiments by organism type, space conditions, and biological outcomes. The platform offers AI-generated summaries, interactive trend graphs, knowledge maps, and dynamic semantic search, facilitating quick identification of research trends, knowledge gaps, and important findings impacting space biology.

How we built it

The project is built using a Flask/Django backend for data processing and API handling, combined with a React.js frontend for a responsive user interface. AI tools, including OpenAI GPT APIs and Hugging Face Transformers, extract and summarize key information from NASA publications. Knowledge graphs capture relationships among organisms, conditions, and outcomes, while D3.js and Plotly libraries power interactive visualizations. Data sources include NASA’s Bioscience Publications Repository and public space biology datasets.

Challenges we ran into

Key challenges included processing and summarizing a large corpus of diverse scientific documents, which required advanced natural language processing and entity extraction. Designing an efficient semantic search to handle varied user queries also required extensive iteration and tuning. Additionally, balancing real-time interactivity with complex, resource-intensive visualizations on the dashboard demanded careful optimization of frontend and backend performance.

Accomplishments that we're proud of

We successfully aggregated and normalized over 600 NASA bioscience publications into a single structured platform, enabling users to uncover actionable insights from fragmented data. The AI-driven summarization and knowledge graph features provided novel ways to explore and understand complex biological relationships in space research. The interactive visualizations received positive feedback for enhancing the accessibility and usability of space science data.

What we learned

The project deepened our expertise in full-stack development, advanced AI application for natural language processing, and interactive data visualization design. We learned how to integrate multiple AI frameworks, manage large-scale scientific datasets, and build knowledge graphs that enable semantic connections. Additionally, challenges in performance optimization and UX design improved our skills in delivering a scalable and user-friendly platform.

What's next for Genome Hub

Future plans include expanding data sources to incorporate more diverse NASA and space agency datasets, improving AI models for deeper semantic understanding and predictive analytics. We aim to add enhanced collaboration features for researchers and mission planners, and incorporate advanced visualization techniques to better reveal biological pathways and mechanisms affected by spaceflight. Long-term, Genome Hub strives to become an essential tool for precision space medicine and mission planning, accelerating discoveries in space bioscience.