
This is an end-to-end bioinformatics data analysis platform designed to simplify biological data management and computational analysis for researchers. The platform solves the critical challenge of processing and analyzing complex biological datasets without requiring extensive programming knowledge. Core Features Data Management System: Users can upload multiple dataset types (CSV, TSV, TXT files up to 100MB) including gene expression, microbiome, protein, and metabolomics data. The system automatically parses, validates, and previews datasets with intelligent column detection and type inference. Advanced Analysis Capabilities: The platform integrates Python-based analysis services that perform statistical analysis (mean, median, standard deviation, quartiles, skewness, kurtosis), correlation analysis (Pearson and Spearman methods), differential expression analysis with p-value thresholds, and K-means clustering with PCA visualization. User Management: Implements role-based access control with researcher and admin roles, secure JWT authentication, and personal workspace management. Each user can maintain private datasets or share them publicly with the research community. Architecture: Built with a modern MERN stack (MongoDB, Express, React, Node.js) for the backend and frontend, plus a separate Flask-based Python microservice handling computationally intensive ML/statistical operations. The frontend features a responsive, mobile-optimized UI using React and Tailwind CSS, while the backend manages datasets, user authentication, and coordinates analysis requests.
19 Nov 2025