Git Product home page Git Product logo

AlphaCryo4D v0.1.1 Development Version

==================================================

AlphaCryo4D is an open-source free software released under GNU General Public LICENSE that implements 3D classification of single-particle cryo-EM data using deep manifold learning and novel energy-based particle voting methods (originally proposed in the following publication). AlphaCryo4D v0.1.1 is currently a development version, NOT a stable released version. The authors are currently optimizing the code architecture and adding novel features to the system. The future version of this open-source software will be updated with a user-friendly interface. Users are free to use and modify the source code, providing their compliance with the GPL and that any publication making use of this software shall cite the following publication:

Reference:

Zhaolong Wu, Enbo Chen, Shuwen Zhang, Yinping Ma, Youdong Mao. Visualizing conformational space of functional biomolecular complexes by deep manifold learning. Int. J. Mol. Sci. 23(16), 8872 (2022). https://doi.org/10.3390/ijms23168872

References of potentially used software:

EMAN2: Tang, G., Peng, L., Baldwin, P. R., Mann, D. S., Jiang, W., Rees, I., & Ludtke, S. J. EMAN2: an extensible image processing suite for electron microscopy. J Struct Biol, 157(1), 38-46 (2007). doi:10.1016/j.jsb.2006.05.009

RELION: Scheres, S. H. RELION: implementation of a Bayesian approach to cryo-EM structure determination. J Struct Biol, 180(3), 519-530 (2012). doi:10.1016/j.jsb.2012.09.006

==================================================

Installation:

It is recommended to install EMAN2 and RELION before using AlphaCryo4D according to the websites https://github.com/cryoem/eman2 and https://github.com/3dem/relion respectively.

  1. Download the source code:

git clone https://github.com/AlphaCryo4D/AlphaCryo4D.git

cd AlphaCryo4D/

  1. Create the conda environment:

conda create -n AlphaCryo4D python=3.7.1

  1. Activate the environment:

source activate AlphaCryo4D

  1. Install the dependencies:

conda install --yes --file EnvConda.txt

pip install -r EnvPip.txt

==================================================

Documentation:

Programs and scripts are described in Docs/documentation_alphacryo4d.pdf. An example tutorial is provied in Docs/tutorial_alphacryo4d.pdf. The procedures are tested on the operating system of CentOS Linux release 7.6.1810. Please do not hesitate to reach our team should you encounter issues in using this system.

==================================================

The AlphaCryo4D Development Team:

Youdong Mao (PI), Zhaolong Wu, Shuwen Zhang, Yinping Ma, Wei Li Wang, Deyao Yin. (May 2022).

==================================================

Copyright ©2022 | The AlphaCryo4D Development Team

Cryo4D 's Projects

alphacryo4d icon alphacryo4d

A deep manifold learning framework for 4D cryo-EM data processing for simultaneous determination of high-resolution structures and dynamics of macromolecules.

rome icon rome

The ROME (Refinement and Optimization via Machine lEarning for cryo-EM) software package is a parallel computing software system dedicated for high-resolution cryo-EM structure determination and data analysis, which implements advanced machine learning approaches in modern computer sciences and runs natively in an HPC environment. The ROME 1.0 introduces SML (statistical manifold learning)-based deep classification following MAP-based image alignment. It also implemented traditional unsupervised MAP-based classification and includes several useful tools, such as 2D class averaging with CTF (contrast transfer function) correction and a convenient GUI for curation, inspection and verification of single-particle classes. The ROME system has be optimized on both Intel® Xeon multi-core CPUs and Intel® Xeon Phi many-core coprocessors.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.