Chan Zuckerberg Initiative EOSS4 Award

MDAnalysis is excited to announce that we have been awarded an Essential Open Source Software for Science (EOSS) grant by the Chan Zuckerberg Initiative for our proposal “MDAnalysis: Faster, extensible molecular analysis for reproducible science”.

Over the next two years, this award will fund work on two major aims that will improve MDAnalysis for our users and make it easier for scientists to contribute code, with a view towards increasing code reuse, interoperability, and reproducibility:

(1) Improving the performance of essential core components by rewriting Python code in Cython

As MDAnalysis has now become a mature library with a stable API, we want to focus on improving the performance of core library components by rewriting essential code in Cython. This will enable us to handle the increasingly large and complex datasets generated to solve the biomedical challenges of tomorrow.

(2) Launching the “MDAKits” ecosystem

We will launch the MDAnalysis Toolkits (“MDAKit”) ecosystem. Inspired by SciPy’s SciKits, an MDAKit will contain code based on MDAnalysis that solves specific scientific problems. An MDAKit can be written by anyone and hosted anywhere. In order to streamline the process we will provide a cookiecutter-based template repository. MDAKits will have a well-defined API, have documentation, will be registered with MDAnalysis, and will be continuously tested for compatibility with the current version of MDAnalysis. As part of the registration process, code will be reviewed by MDAnalysis developers and we will encourage the scientific publication of the package, e.g., in the Journal of Open Source Software. We will also refactor a number of analysis modules as separate MDAKits. Overall, the introduction of MDAKits will enable the rapid development and dissemination of new components and tools that can be released independently of the main package. We will soon describe the details of MDAKits in a white paper and seek a discussion with the wider community. Ultimately, MDAKits should help address two long-standing challenges in the biomolecular simulation community: effort duplication and reproducibility.

Along the same lines, we will focus on software interoperability with other packages by expanding our converters framework.

By validating, maintaining and publicizing new code through a common process, we encourage scientists to reuse and extend existing packages rather than re-creating their own ones. We hope that this combined approach will improve consistency, transparency, and accessibility in methods used across scientific studies.

This project will be led by Irfan Alibay, Lily Wang, Fiona Naughton, Richard Gowers, and Oliver Beckstein.

About MDAnalysis

The MDAnalysis package is one of the most widely used Python-based libraries for the analysis and manipulation of molecular simulations. The objective of MDAnalysis is to provide simple, flexible, and efficient means of handling molecular structure data from simulations and experiments and support research in biophysics, biochemistry, materials science and beyond.

MDAnalysis is a fiscally-sponsored project of NumFOCUS, a nonprofit dedicated to supporting the open source scientific computing community.