This repository provides a Visual Studio Code development container specifically tailored for computational biology and bioinformatics research. The container includes two primary environments:
- Python Environment (
py_env): This environment is equipped with CUDA support, making it ideal for handling computations that benefit from GPU acceleration. - R Environment (
r_env): This environment includes RStudio Server, providing a robust platform for statistical computing and graphics.
- CUDA Integration: Accelerate your data processing and model training with the power of GPU computing.
- RStudio Server: Access a powerful IDE for R, directly within your development environment, enhancing productivity and collaboration.
To use this devcontainer, ensure that you have Visual Studio Code and the Remote - Containers extension installed. Clone this repository and open it in VSCode. Then, follow the prompt to reopen the project in the containerized environment, allowing you to access pre-configured settings and tools for your research.