justinGilmer / cybercamp

Rapid overview of molecular simulation

Cybercamp

The cybercamp is rapid overview of molecular simulation and the underlying tools.

Overview

This repository is designed to provide users the resources to quickly get up to speed with molecular simulations. This will not only include information needed to better understand simulations, but it will also provide specific information for workflow management, "sandboxed" development environments, python specific scientific packages, etc.

Getting Started

Prerequisites

• miniconda

  • A python package mangement tool, useful for creating clean, reproducible development environments

• Command line familiarity

  • Most of the interaction with simulation programs involves some knowledge of the GNU/Linux, or Unix command line interface.

  • A useful guided tutorial for the command line can be found here.

• Visualization tools

  • Humans are much more adept at visually inspecting data when it is presented properly. We are not great at reading a large data file and developing any meaningful hypotheses/conclusions from a list of numbers. We are much better at looking at plot of the data, or rendering the trajectory of a molecule evolving in space and time.
  • To do this we require molecular visualization tools and data visualization tools
  • For molecular visualization, a common choice is VMD
  • A common pythonic choice for data visualization is Matplotlib and can easily be installed via anaconda

Installing

To get a working development environment that uses the MoSDeF toolkit, HOOMD-Blue for simulation, Matplotlib for data visualization, and signac and signac-flow for workflow management, we will use conda we installed earlier.

Update conda

conda update conda

Add the mosdef, conda-forge, and omnia channels for conda to search through when installing packages.

conda config --add channels mosdef
conda config --add channels conda-forge
conda config --add channels omnia

Create a new python 3.6 development environment named simulation36 that includes many of the packages needed to build systems, run simulations, and analyze the data.

conda create -n simulation36 python=3.6 mbuild foyer hoomd matplotlib signac signac-flow fresnel gsd freud jupyter py3dmol

Activate the environment

conda activate simulation36

# install openbabel now, to prevent segmentation faults trying to install it above
conda install -y -c conda-forge openbabel

Content

Computational Basics

The following links provide an overview of the use of the unix/linux shell, Python, and plotting using matplotlib.

• Introduction to the Unix shell: http://swcarpentry.github.io/shell-novice/
• Introduction to Python: http://swcarpentry.github.io/python-novice-inflammation/
• Plotting and Programming in Python: http://swcarpentry.github.io/python-novice-gapminder/
• Analysis and plotting Python scripts: https://github.com/PTC-CMC/plotting

Molecular Modeling and Simulation

• Introduction to Simulation
• Introduction to Molecular Dynamics
• Anatomy of a Script File
• Neighborlists and Dangerous Builds
• Timestep Optimization
• Introduction to GROMACS

Other resources

• Introduction to version control with git: http://swcarpentry.github.io/git-novice/
• Using Jupyter notebooks:
  • http://jupyter.readthedocs.io/en/latest/
  • https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/
  • https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook
• Brief guides on GitHub and git workflows: https://guides.github.com/
• Introduction to version control with git: http://swcarpentry.github.io/git-novice/
• Full list of software carpentry lessons: https://software-carpentry.org/lessons/
• Bevan Lab GROMACS Tutorials: http://www.mdtutorials.com/gmx/

Primary Authors

• Christopher R. Iacovella
• Justin Gilmer
• Andrew Z. Summers

License

This project is licensed under the MIT License - see the LICENSE.md file for details