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== EMAN 2.2 == = EMAN2.2 Release Notes =
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Please note that while there is an experimental EMAN 2.2 binary download for Linux, we are designing a new binary installation framework at the moment, so there isn't a proper stable 2.2 release just yet. We will update this page (and elsewhere) when things have stabilized. If you are anxious to play with 2.2, at present the best strategy is to compile from source directly from GitHub. There is an all new strategy for building from source on the Mac, which is quite straightforward (unlike the old method), and standard methods should still work on Linux. This is not an all-inclusive list, it includes only the more interesting/useful changes since EMAN2.12

=== Single Particle Analysis ===
 * Many, deep improvements to refinement
  * Substantial refinement changes and new filtering techniques
  * Optional tophat filter (similar to Relion post processing), side chains often look even better than Relion
 * Local resolution and filtration
  * can be enabled in refinement to provide local detail appropriate to local resolution
 * Several new methods for conformational/compositional heterogeneity
  * Including multi-model refinement with or without alignment, masked particle subtraction, 2-D and 3-D Deep Learning approaches
 * New bad particle identification strategy
  * Proven to produce better maps in several projects!
 * Automatic CTF
  * Used to be several manual steps. Entire process now automated.
  * Easy and fast refinement at progressive resolutions
 * New e2boxer (particle picker)
  * Fixes the problems with the old particle picker
  * New (optional) neural network picker for difficult projects
 * Stochastic Gradient Descent initial model generator (experimental)
 * Automatic magnification anisotropy correction tool
  * Post-processing program which corrects for the common microscope anisotropy problem on FEI scopes
  * Automatic, does not require additional data collection
 * New direct detector movie aligner
  * All new program. Competitive with other alignment programs in quality
  * Workflow for handling movies in EMAN2 projects


=== Subtomogram Averaging ===
 * New subtomogram averaging tools
  * New pipelines for subtomogram averaging and classification
 * Up to 20x faster 3-D alignments,
  * now practical to study 10,000 300x300x300 particles on a single workstation
 * New automatic missing wedge identification/compensation in alignment/averaging

=== Tomogram Segmentation ===
 * Workflow for semi-automatic tomogram annotation/segmentation
  * Uses convolutional neural network technology with user guided training of features.

=== Overall Changes ===
 * Anaconda Python based distribution
  * Integrates !SciPy, Theano, !PyLearn and other toolkits
 * !GitHub
  * Source code is now managed via a public !GitHub repository (cryoem/eman2)
 * Windows 10/7 64 bit
  * Initial support, poorly tested, but available for the first time (EMAN2 only, SPARX/SPHIRE do not support this platform)

EMAN2.2 Release Notes

This is not an all-inclusive list, it includes only the more interesting/useful changes since EMAN2.12

Single Particle Analysis

  • Many, deep improvements to refinement
    • Substantial refinement changes and new filtering techniques
    • Optional tophat filter (similar to Relion post processing), side chains often look even better than Relion
  • Local resolution and filtration
    • can be enabled in refinement to provide local detail appropriate to local resolution
  • Several new methods for conformational/compositional heterogeneity
    • Including multi-model refinement with or without alignment, masked particle subtraction, 2-D and 3-D Deep Learning approaches
  • New bad particle identification strategy
    • Proven to produce better maps in several projects!
  • Automatic CTF
    • Used to be several manual steps. Entire process now automated.
    • Easy and fast refinement at progressive resolutions
  • New e2boxer (particle picker)
    • Fixes the problems with the old particle picker
    • New (optional) neural network picker for difficult projects
  • Stochastic Gradient Descent initial model generator (experimental)
  • Automatic magnification anisotropy correction tool
    • Post-processing program which corrects for the common microscope anisotropy problem on FEI scopes
    • Automatic, does not require additional data collection
  • New direct detector movie aligner
    • All new program. Competitive with other alignment programs in quality
    • Workflow for handling movies in EMAN2 projects

Subtomogram Averaging

  • New subtomogram averaging tools
    • New pipelines for subtomogram averaging and classification
  • Up to 20x faster 3-D alignments,
    • now practical to study 10,000 300x300x300 particles on a single workstation
  • New automatic missing wedge identification/compensation in alignment/averaging

Tomogram Segmentation

  • Workflow for semi-automatic tomogram annotation/segmentation
    • Uses convolutional neural network technology with user guided training of features.

Overall Changes

  • Anaconda Python based distribution
    • Integrates SciPy, Theano, PyLearn and other toolkits

  • GitHub

    • Source code is now managed via a public GitHub repository (cryoem/eman2)

  • Windows 10/7 64 bit
    • Initial support, poorly tested, but available for the first time (EMAN2 only, SPARX/SPHIRE do not support this platform)

EMAN2/Eman22Release (last edited 2021-03-31 03:45:14 by SteveLudtke)