Most of the pages are editable by any user that has registered an account on the server. To prevent spam, you need to email firstname.lastname@example.org to get an account on the system if you wish to contribute changes. If you just wish to browse, you don't need an account.
EMAN2 is the successor to EMAN1. It is a broadly based greyscale scientific image processing suite with a primary focus on processing data from transmission electron microscopes. EMAN's original purpose was performing single particle reconstructions (3-D volumetric models from 2-D cryo-EM images) at the highest possible resolution, but the suite now also offers support for single particle cryo-ET, and tools useful in many other subdisciplines such as helical reconstruction, 2-D crystallography and whole-cell tomography. EMAN2 is capable of processing very large data sets (>100,000 particle) very efficiently.
Please also note that this is not the (related) EMEN2 electronic notebook, but is EMAN2, a scientific image processing suite.
EMAN is free software, supported by NIH Grants. It is critical that you cite EMAN2 when you use it in a publication in any significant way, to help us document usage when trying to renew our funding. Feel free to cite any of these:
Primary EMAN2 paper:
G. Tang, L. Peng, P.R. Baldwin, D.S. Mann, W. Jiang, I. Rees & S.J. Ludtke. (2007) EMAN2: an extensible image processing suite for electron microscopy. J Struct Biol. 157, 38-46. PMID: 16859925
EMAN2 high resolution refinement methods:
J.M. Bell, M. Chen, P.R. Baldwin & S.J. Ludtke. (2016) High Resolution Single Particle Refinement in EMAN2.1. Methods. 100, 25-34. PMC4848122
Methods for analysis of conformational and compositional variability:
- Ludtke, S. J. "Single-Particle Refinement and Variability Analysis in EMAN2.1." in Methods Enzymol 579159-189 (Elsevier, United States, 2016). PMC5101015
Methods for subtomogram averaging:
J.G. Galaz-Montoya, C.W. Hecksel, P.R. Baldwin, E. Wang, S.C. Weaver, M.F. Schmid, S.J. Ludtke & W. Chiu. (2016) Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography. J Struct Biol. 194, 383-394. PMC4846534
Installation Guides (binary and source)
We prefer to provide assistance via the Google group below, since this archives all discussions and makes them searchable. You must join the group to post, but can browse old content anonymously.
http://groups.google.com/group/eman2 (Main discussion list for EMAN2)
http://groups.google.com/group/eman2-developers (Discussions among developers, likely less interesting for users)
FAQ - Please ask your questions in the Google Group which has a searchable archive. This page is somewhat out of date
NOTE - If you are located in a country that blocks Google (China) or prefer not to post publicly, please feel free to email email@example.com directly. The Google Group is used because it creates a persistent searchable archive of past questions, but direct emails are completely acceptable.
- User Documentation
File Descriptions (Folders and files in an EMAN2 Project)
Standards (File Formats, Symmetry, Box Size, etc.)
Programs (Individual Program Documentation)
Clusters (Running EMAN2 on clusters and multi-core workstations)
GPGPU Computing (use the graphics processor for image processing)
Old Docs (Out of date documentation)
Advanced Users & Programmers (Python)
EMAN2 is the successor to EMAN1. It is a broadly based greyscale scientific image processing suite with a primary focus on processing data from transmission electron microscopes. EMAN's original purpose was performing single particle reconstructions (3-D volumetric models from 2-D cryo-EM images) at the highest possible resolution, but the suite now also offers support for single particle cryo-ET, and tools useful in many other subdisciplines such as helical reconstruction, 2-D crystallography and whole-cell tomography. Image processing in a suite like EMAN differs from consumer image processing packages like Photoshop in that pixels in images are represented as floating-point numbers rather than small (8-16 bit) integers. In addition, image compression is avoided entirely, and there is a focus on quantitative analysis rather than qualitative image display.
All EMAN2 programs, including GUI programs, are written in the easy-to-learn Python scripting language. This permits knowledgeable end-users to customize any of the code with unprecedented ease. If you aren't an advanced user, you can still make use of the integrated GUI and all of EMAN2's command-line programs.