# RaptGen-UI: an integrated platform for exploring and analyzing the sequence landscape of HT-SELEX experiments

## TL;DR

RaptGen-UI is a user-friendly platform for analyzing RNA aptamer data from HT-SELEX experiments using machine learning and visualization tools.

## Contribution

The novel contribution is an integrated, containerized platform with GPU support for HT-SELEX analysis accessible to non-computational researchers.

## Key findings

- RaptGen-UI enables efficient HT-SELEX dataset analysis and RNA aptamer optimization.
- The platform supports secure local deployment with GPU or CPU environments.
- It is freely available with open-source code and documentation.

## Abstract

RaptGen-UI provides intuitive graphical user-interface of the system exploring and analyzing the sequence landscape of high-throughput (HT)-SELEX (Systematic Evolution of Ligands by EXponential enrichment) experiments through machine learning-driven visualization with optimization capabilities. This software enables wet-lab researchers to efficiently analyze HT-SELEX dataset and optimize RNA aptamers without requiring extensive computational expertise. The containerized architecture ensures secure local deployment and supports both of high-performance Graphics Processing Unit (GPU) acceleration and CPU-only environments, making it suitable for various research settings.

This software is a web-based application running locally on the user’s PC. The frontend is constructed using Next.js and Plotly.js with TypeScript, while the backend is developed using FastAPI, Celery, PostgreSQL RDBMS, and Redis with Python. Each module is encapsulated within Docker containers and deployed via Docker Compose. The system supports both CUDA GPU and CPU-only environments. Source code and documentation are freely available at https://github.com/hmdlab/RaptGen-UI.