Abstract
Computational pipelines have become a crucial part of modern drug discovery campaigns. Setting up and maintaining such pipelines, however, can be challenging and time-consuming --- especially for novice scientists in this domain.
TeachOpenCADD is a platform that aims to teach domain-specific skills and to provide pipeline templates as starting points for research projects. We offer Python-based solutions for common tasks in cheminformatics and structural bioinformatics in the form of Jupyter notebooks and based on open source resources only. Including the 12 newly released additions, TeachOpenCADD now contains 22 notebooks that each cover both theoretical background as well as hands-on programming.
To promote reproducible and reusable research, we apply software best practices to our notebooks such as testing with an automated continuous integration and adhering to a more idiomatic Python style. The new TeachOpenCADD website is available at https://projects.volkamerlab.org/teachopencadd and all code is deposited on GitHub.
Supplementary weblinks
Title
TeachOpenCADD's official website
Description
This website hosts a static view of TeachOpenCADD's
Jupyter notebooks, allowing users to interact with the material in a read-only manner. Instructions on installation and contributions are also published here.
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TeachOpenCADD's GitHub repository
Description
This GitHub repository hosts all TeachOpenCADD-related code, incl. the Jupyter notebooks, the command-line interface, the continuous integration, the TeachOpenCADD website, and more.
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