Reproducibility

7. tb-rbfe-setup

Contains files and scripts necessary to reproduce some of the mutations in this paper.

This repository contains the raw data tables used in this paper. Its aim is to ensure that the results can be reproduced by other people and therefore a Jupyter notebook is included that allows one to recreate nearly all the figures and tables in the manuscript from the raw data tables. It is also setup to run in browser using the wonderful MyBinder service.

5. cryptic-ecoffs

This repository contains a jupyter notebook that reads in the raw data from the CRyPTIC project and reproduces the vast majority of the Tables and Figures from this paper. It is setup to run in browser using the MyBinder service.

4. amr-free-energy-examples

This GitHub repository contains a set of example GROMACS input files that allows you to reproduce a set of free energy calculations, as described in this paper. Shell scripts are included to simplify launching and analysing the GROMACS simulations.

3. calculate-bilayer-power-spectrum

This GitHub repository contains the key Python code for calculating the undulation and thickness power spectra of large lipid bilayers (like the one below). It was introduced in this paper and then also used here and here. Like the other repositories, it contains a tutorial and some sample data allowing you to reproduce one of the figures from the original paper.

2. alchembed-tutorial

This GitHub repository accompanies this paper. It explains how you can use the soft-core van der Waals functionality in GROMACS to rapidly embed proteins (or anything else, such as benzene rings as shown below) in membranes. To simplify the process, a series of shell scripts are included that call GROMACS.

1. fd169-image-processing-example

This GitHub repository accompanies this paper and walks you through using image processing in Python to examine phase separation in a bilayer containing three very different species of lipids. A subsequent paper relied on the same approach.