Skip to content
In GSoC 2026

MDAnalysis

MDAnalysis is a Python library for the analysis of computer simulations of many-body systems at the molecular scale, spanning use cases from interactions of drugs with proteins to novel materials. It is written by scientists for scientists and is used for cutting edge research in biophysics, chemistry, soft-matter physics, and materials research around the world in academia and national research labs. MDAnalysis strives to be highly interoperable and hence a growing number of projects use MDAnalysis as their foundational library or integrate it.

Contributors in 2026

3

−1 from 2025

Projects since 2016

19

2.7 a cycle on average

Cycles

7 of 11

7-cycle streak

Rank in 2026

#119

of 183, 0.3% of slots

Mentors

9

for 4 projects in 2025

Contributors per cycle

Accepted projects each year, against the median organization that year

  1. 4
  2. 3
View as table
MDAnalysis contributors per cycle
MDAnalysisMedian organization
201604
201704
201803
201904
202034
202124
202223
202324
202434
202545
202634

Stack and topics

Each one has its own page of organizations and trends

More about MDAnalysis

The goal of MDAnalysis is to make it easy for users to analyze data that are produced by simulations (primarily molecular dynamics simulations) that run on some of the largest supercomputers in the world. MDAnalysis accomplishes this goal by providing a toolkit of programming building blocks that provide an abstract Python interface to the simulation data — agnostic of the specific simulation package that produced it — that lends itself to interactive data exploration and rapid prototyping but is also a robust foundational library that can form the basis for new computational tools.

MDAnalysis allows one to read particle-based trajectories such as the ones produced by MD simulations or individual coordinate frames (such as biomolecules in the Protein Databank format) and access the atomic coordinates through NumPy arrays. Together with a powerful selection language and many implemented analysis algorithms, MDAnalysis provides a flexible and fast framework for complex analysis tasks. Welcoming documentation such as the User Guide https://userguide.mdanalysis.org/ make it easy to get started. New releases are downloaded a few thousand times and the academic papers describing MDAnalysis are cited more than almost two thousand times, indicating the widespread use in the academic community.

Quick answers

Is MDAnalysis in GSoC 2026?
Yes, with 3 contributors.
How long has it taken part?
7 of 11 cycles since 2016, first in 2020, with a 7-cycle streak running.
How many contributors does it usually take?
2.7 a cycle on average, 19 in total. Its largest cycle was 2025, with 4.
What does it build with?
Python, Cython, C, C++, NumPy, C/C++.

Accepted projects

3 projects in 2026 · All 19 projects since 2016

  1. Adding Additional Functionality and Enhancements to the Fetcher Module

    jauy123

    A major goal for MDAnalysis 3.0 is the “support for streaming and cloud stor- age.”1. A natural extension of this object simply adding the ability to...

  2. Interface for post-simulation analysis (“crawling”) of WESTPA simulations

    Kunj Sinha

    This project aims to implement a WESTPAParser and a WESTPAReader in WESTPA which will expose WESTPA’s HDF5 Framework simulation data as a standard...

  3. Dashboard for tracking MD simulation progress with the new streaming interface

    Pardhav Maradani

    This project will develop a browser-based, real-time dashboard for molecular dynamics simulations using the new IMDv3 streaming protocol, enabling...

No accepted proposals or progress posts from MDAnalysis contributors yet. Contributed here? Share yours.

Claim your project

Data: Google Summer of Code public archive. Contributor counts are accepted projects.