OTPD for ALS
A bioinformatics platform designed for ALS drug target discovery, heavily utilizing multi-omics analysis and large-scale data pipelines.
The Open Target Prediction Dashboard (OTPD) for ALS is an open-source platform I built to accelerate drug discovery for neurodegenerative diseases.
The Challenge
ALS is a complex, multifactorial disease where single-gene approaches often fail in clinical trials. Researchers needed a centralized way to synthesize complex multi-omics data (RNA-seq, proteomics, and genomic data) to evaluate and score potential drug targets efficiently.
The Solution
I architected and developed a full-stack bioinformatics platform using Next.js and Node.js, providing an intuitive, high-performance interface for researchers to query, visualize, and analyze complex biological datasets.
Key Contributions
- Full-Stack Architecture: Engineered the entire platform from the ground up, building a highly responsive Next.js frontend and a robust Node.js backend to handle complex data querying.
- Data Sourcing & Pipelines: Built efficient Node.js data pipelines to systematically source, clean, and standardize large-scale multi-omics data from public databases like PubChem and Open Targets.
- Data Visualization: Implemented interactive and highly performant data visualization components, enabling researchers to easily interpret dense bioinformatics data.
- Workflow Optimization: Centralized diverse biological datasets into a unified dashboard, drastically reducing the time required for researchers to identify high-confidence targets.