EMAN Home
There are 2 versions of EMAN
Please select:
| EMAN1 (Stable) | (download) |
| EMAN2 (now stable!) | (download) |
Which link to follow ?
EMAN2 is now about a 90% replacement for EMAN1. It has full 2D and 3D refinement capabilities, and has produced structures now being published. There are a few features which still haven't been ported, and for these, it is simple to install EMAN1 along-side EMAN2, so they can be used simultaneously. EMAN2 is completely Python-based, allowing end-users to easily write their own scripts or modify existing scripts. EMAN2 is now stable enough for end-users to try and there are complete tutorials in the Wiki to get you started. There is an integrated workflow, which is recommended for both beginners and advanced users, as it will take you through many common tasks, and insure that all information about the processing is properly logged in an embedded database system.
What is EMAN ?
EMAN is a suite of scientific image processing tools aimed primarily at the transmission electron microscopy community, though it is beginning to be used in other fields as well. EMAN has a particular focus on performing a task known as single particle reconstruction. In this method, images of nanoscale molecules and molecular assemblies embedded in vitreous (glassy) ice are collected on a transmission electron microscope, then processed using EMAN to produce a complete 3-D recosntruction at resolutions now approaching atomic resolution. For low resolution structures (~2 nm), this may require ~8 hours of computer processing and a few thousand particles. For structures aimed at ~0.5 nm or better resolution, hundreds of thousands of particles and hundreds of thousands of CPU-hours (on large computational clusters) may be required. Indeed, EMAN is often used in supercomputing facilities as a test application for large-scale computing.
Scientific image processing is distinguished from typical 'Photoshop' image processing in that it is analyitical in nature. Images processed in EMAN are floating point greyscale images. That is, the pixel values in the images are represented as real numbers, not as small integers (typical GIF/JPG/PNG images are limited to integral values from 0-255 for each pixel). Processing often includes complex image processing operations in Fourier or Wavelet space. EMAN was first released in 1999, and has been under continuous development since. It consists of a C++ library of hundreds of different image/volume processing algorithms with bindings into the popular Python scripting language. In new EMAN development, all user-level programs (of which there are over 200 in EMAN 1.8) are developed in Python, allowing the knowledgable end-user to make modifications without having to download or compile any of the C++ source code.
Last modified by Steven Ludtke 09/28/2006
