DeerAnalysis 2026 is major re-design and re-release of the popular dipolar-EPR data processing tool, DeerAnalysis. DeerAnalysis was originally released in 2006, as a matlab based GUI for Tikhnov-regularisation based approaches for extracting distance distributions from Double-Electron-Electron-Resonance (DEER) data, it has been updated multiple times since then most recently in 2022. In xxx DeerAnalysis gained support for neural-network based fitting in the form of DeerNet.
In the 2026 release, DeerAnalysis moved to a modern Python and Javascript based software stack, gaining support for multi-pathway fitting, compactness criterion for non-parametric models, and a completely redesigned user interface. Additionally, a new data/fit management software was implemented, allowing users to easily manage and compare multiple datasets and fits. Support for DeerNet was retained. The parametric and non-parametric fitting is powered by the latest version of DeerLab, which is also available as a standalone package for Python.
- Regularisation and parametric based fitting now using the latest DeerLab 1.2
- Dataset and fit managment, with high-quality comparison
- Based on a modern software stack (Python and Javascript)
- Compiled support on all major operating Systems
- Multi-pathway support (from DeerLab)
- Support for compactness criterion for non-parametric models (DeerLab)
- Support for global and population based fitting (DeerLab)
DeerAnalysis 2026 is avaliable in pre-compiled binaries for Windows, Mac and Linux. The latest release can be found on the GitHub releases page. There is no need to install Python or any dependencies, simply download the latest release for your operating system and run the executable.
When you use DeerAnalysis in your work, please cite the following publications:
DeerLab: a comprehensive software package for analyzing dipolar electron paramagnetic resonance spectroscopy data
Luis Fábregas Ibáñez, Gunnar Jeschke, Stefan Stoll
Magn. Reson., 1, 209–224, 2020
doi.org/10.5194/mr-1-209-2020
Deep neural network processing of DEER data
Steven G. Worswick, James A. Spencer, Gunnar Jeschke, Ilya Kuprov'
Science Advances 2018
doi.org/10.1126/sciadv.aat5218
DeerAnalysis is licensed under the MIT License.
Copyright (c) 2026 by the Jeschke Lab, ETH Zurich. All rights reserved.