Exercises and course material from the Computing Environments course of my Master's in Bioinformatics.
This repository contains the content, notes, and exercises developed throughout the Computing Environments course. The goal is to build a solid foundation in python and practices used to work efficiently and reproducibly in computational biology.
Folder names are examples and may change as the course progresses.
- Clone the repository
git clone https://github.com/your-username/computing-environments.git
cd computing-environments- Create the environment (when an
environment.ymlis provided)
conda env create -f environment.yml
conda activate computing-environmentsEach exercise includes:
- A description of the problem
- The solution (scripts, notebooks, or commands)
- Notes on how to run it and the expected output
This work is part of the Master's program in Bioinformatics at Federal University of Minas Gerais, in the course Computing Environments, taught by Raquel Cardoso de Melo Minardi during 2/2026.
The solutions here reflect my own understanding and were created for learning purposes. If you are currently taking this course, use them as a reference, not as a substitute for doing the exercises yourself.
Nathan Bryce
This project is licensed under the MIT License.