assets.json

{
  "containers": {
    "jupyterhub-base": {
      "latest": "2026-04-13",
      "name": "CCPBioSim Base Image",
      "category": "infrastructure",
      "shortdesc": "CCPBioSim JupyterHub base container for use in other training workshops.",
      "longdesc": ""
    },
    "structure-validation-uglymol": {
      "latest": "2026-04-13",
      "name": "Uglymol Image",
      "category": "infrastructure",
      "shortdesc": "Uglymol container for hosted deployment as part of the structure validation workshop.",
      "longdesc": ""
    },
    "structure-validation-workshop": {
      "latest": "2026-04-13",
      "name": "An Introduction to Structure Validation",
      "category": "setup",
      "shortdesc": "This course will introduce methods to deduce that starting structures for preparing simulations represent high quality starting points.",
      "longdesc": ""
    },
    "basic-statistics-workshop": {
      "latest": "2026-04-13",
      "name": "Introducing Basic Statistics",
      "category": "analysis",
      "shortdesc": "This course illustrates how basic statistical concepts can be applied to the analysis of biomolecular simlation data",
      "longdesc": ""
    },
    "aiida-lysozyme-workshop": {
      "latest": "2026-04-13",
      "name": "aiida-gromacs - Lysozyme MD simulation tutorial",
      "category": "setup",
      "shortdesc": "Data provenance tools demonstrated with Justin Lemkul's lysozyme in water simulation tutorial.",
      "longdesc": ""
    },
    "basic-analysis-workshop": {
      "latest": "2026-04-13",
      "name": "Introducing Basic Analysis",
      "category": "analysis",
      "shortdesc": "In this course we will explore some of the issues in simulation preparation and analysis that can trip up the unwary, and how to avoid them.",
      "longdesc": ""
    },
    "equilibration-workshop": {
      "latest": "2026-04-13",
      "name": "An Introduction to Equilibration",
      "category": "setup",
      "shortdesc": "This course looks at one of the most common methods for assessing equilibration: the calculation of RMSDs. It may be a common approach, but is it a good one? Maybe not.",
      "longdesc": ""
    },
    "ubiquitin-analysis-workshop": {
      "latest": "2026-04-13",
      "name": "Introduction to Analysis of Ubiquitin",
      "category": "analysis",
      "shortdesc": "This course illustrates the application of a number of Python-based tools to the analysis of the results from a short (1 nanosecond) simulation of ubiquitin, investigating the question, how similar is the MD trajectory to the crystal and NMR structures?",
      "longdesc": ""
    },
    "clustering-workshop": {
      "latest": "2026-04-13",
      "name": "An Introduction to Clustering",
      "category": "analysis",
      "shortdesc": "This course illustrates the application of a variety of clustering methods to an MD trajectory, comparing their performance.",
      "longdesc": ""
    },
    "aiida-gpcr-workshop": {
      "latest": "2026-04-13",
      "name": "aiida-gromacs - GPCR MD simulation tutorial",
      "category": "advanced",
      "shortdesc": "An advanced demonstration showing advanced GPCR workflow with full data provenance collection.",
      "longdesc": ""
    },
    "pca-workshop": {
      "latest": "2026-04-13",
      "name": "An Introduction to Principle Component Analysis",
      "category": "analysis",
      "shortdesc": "The aim of this course is to illustrate methods we can use to assess convergence and sampling in MD trajectories.",
      "longdesc": ""
    },
    "python-workshop": {
      "latest": "2026-04-13",
      "name": "An Introduction to Python Programming",
      "category": "coding",
      "shortdesc": "This course will introduce more intermediate features of Python that are useful for biomolecular modellers.",
      "longdesc": ""
    },
    "pdb2pqr-workshop": {
      "latest": "2026-04-13",
      "name": "An Introduction to PDB2PQR",
      "category": "setup",
      "shortdesc": "This short course illustrates the application of pdb2pqr to the analysis of the tautomeric and ionization states of residues in the structure of the cysteine protease cruzein (PDB code 2oz2) - the results may not be what you would have expected!",
      "longdesc": ""
    },
    "docking-workflow": {
      "latest": "2026-04-13",
      "name": "Introducing Docking Workflows",
      "category": "advanced",
      "shortdesc": "This course introduces docking tools and workflows.",
      "longdesc": ""
    },
    "qmmm-workshop": {
      "latest": "2026-03-23",
      "name": "Introducing QM/MM",
      "category": "advanced",
      "shortdesc": "The course will introduce non-specialists to the use of combined quantum mechanics/molecular mechanics (QM/MM) methods for modelling enzyme-catalysed reaction mechanisms.",
      "longdesc": ""
    },
    "mm-gbsa-workshop": {
      "latest": "2026-04-13",
      "name": "Analysing with MM-GBSA",
      "category": "analysis",
      "shortdesc": "This course walks through the process of perfprming a basic MM-GBSA analysis of a molecular dynamics simulation of a protein-ligand complex to estimate the ligand binding free energy.",
      "longdesc": ""
    },
    "protein-ml-workshop": {
      "latest": "2026-04-13",
      "name": "Protein Analysis with Machine Learning",
      "category": "analysis",
      "shortdesc": "This course introduces the application of Machine Learning methods (specifically, PCA and clustering) to the analysis of protein simulation data.",
      "longdesc": ""
    },
    "protein-analysis-workshop": {
      "latest": "2026-04-13",
      "name": "Introduction to the Analysis of Proteins",
      "category": "analysis",
      "shortdesc": "This course introduces the application of MDTraj to the analysis of protein simulation data.",
      "longdesc": ""
    },
    "protein-preparation-workshop": {
      "latest": "2026-03-23",
      "name": "Preparing Proteins for Simulation",
      "category": "setup",
      "shortdesc": "This course walks through the process of preparing a simple protein system for molecular dynamics simulation using Ambertools.",
      "longdesc": ""
    },
    "dna-workshop": {
      "latest": "2026-03-23",
      "name": "Running DNA Simulations",
      "category": "simulation",
      "shortdesc": "This course introduces tools for running simulations on DNA systems.",
      "longdesc": ""
    },
    "protein-simulation-workshop": {
      "latest": "2026-03-23",
      "name": "Running MD Simulations",
      "category": "simulation",
      "shortdesc": "This workshop demonstrates two approaches to running MD simulations on a simple protein system.",
      "longdesc": ""
    },
    "coarse-graining-workshop": {
      "latest": "2026-04-13",
      "name": "Introducing Coarse-Graining",
      "category": "advanced",
      "shortdesc": "This workshop introduces tools for setup and running coarse-grain simulations.",
      "longdesc": ""
    },
    "openff-workshop": {
      "latest": "2026-03-23",
      "name": "Introducing OpenForceField Tools",
      "category": "advanced",
      "shortdesc": "This workshop introduces the openforcefield tooling.",
      "longdesc": ""
    }
  },
  "software": {
    "codeentropy": {
      "name": "CodeEntropy",
      "shortdesc": "This code is a complete and generally applicable set of tools for computing entropy of macromolecular systems from the forces sampled in a MD simulation.",
      "longdesc": "CodeEntropy is a Python package for computing the configurational entropy of macromolecular systems using forces sampled from molecular dynamics (MD) simulations. It implements the multiscale cell correlation method to provide accurate and efficient entropy estimates, supporting a wide range of applications in molecular simulation and statistical mechanics.",
      "authors": {
        "Arghya Chakravorty": "https://orcid.org/0000-0002-4467-1135",
        "Donald Chung-HK": "",
        "Sarah Fegan": "https://orcid.org/0009-0007-1030-228X",
        "James Gebbie-Rayet": "https://orcid.org/0000-0001-8271-3431",
        "Sarah Harris": "https://orcid.org/0000-0002-2812-1651",
        "Richard Henchman": "https://orcid.org/0000-0002-0461-6625",
        "Jonathan Higham": "https://orcid.org/0000-0002-9779-9968",
        "Jas Kalayan": "https://orcid.org/0000-0002-6833-1864",
        "Ioana Papa": "https://orcid.org/0009-0000-2287-4081",
        "Harry Swift": "https://orcid.org/0009-0007-3323-753X"
      },
      "category": "scientific",
      "image": "codeentropy_logo_grey.svg",
      "github": "https://github.com/CCPBioSim/CodeEntropy",
      "docs": "https://codeentropy.readthedocs.io",
      "pypi": true,
      "conda": true
    },
    "aiida-amber": {
      "name": "aiida-amber",
      "shortdesc": "The AMBER plugin for AiiDA aims to enable the capture and sharing of the full provenance of data when parameterising and running molecular dynamics simulations.",
      "longdesc": "aiida-amber is a plugin that integrates the Amber molecular dynamics software with AiiDA, an open-source framework for automated computational science workflows. Its primary goal is to enable the capture and sharing of the full provenance of data when parameterising and running molecular dynamics simulations. It is being developed as part of the Physical Sciences Data Infrastructure (PSDI) programme to improve data practices within the Physical Sciences in the UK. The plugin is currently a work in progress, with more complete functionality planned for future releases. Its design follows a minimal-disruption philosophy — researchers can gain access to powerful FAIR data practices by simply activating an AiiDA conda environment and making slight modifications to their existing command lines, without needing to make wholesale changes to their workflows.",
      "authors": {
        "Jas Kalayan": "https://orcid.org/0000-0002-6833-1864",
        "James Gebbie-Rayet": "https://orcid.org/0000-0001-8271-3431",
        "Harry Swift": "https://orcid.org/0009-0007-3323-753X"
      },
      "category": "data-tools",
      "image": "aiida-amber-logo.svg",
      "github": "https://github.com/CCPBioSim/aiida-amber",
      "docs": "https://aiida-amber.readthedocs.io",
      "pypi": true,
      "conda": true
    },
    "aiida-gromacs": {
      "name": "aiida-gromacs",
      "shortdesc": "The GROMACS plugin for AiiDA aims to enable the capture and sharing of the full provenance of data when parameterising and running molecular dynamics simulations.",
      "longdesc": "aiida-gromacs is a plugin that integrates the GROMACS molecular dynamics software with AiiDA, an open-source framework for automated computational science workflows. Its primary goal is to enable the capture and sharing of the full provenance of data when parameterising and running molecular dynamics simulations. The plugin is developed as part of the Physical Sciences Data Infrastructure (PSDI) programme, which aims to improve data practices within the Physical Sciences in the UK. A key design principle is minimal disruption to existing workflows — researchers can gain access to powerful FAIR (Findable, Accessible, Interoperable, Reusable) data practices simply by activating an AiiDA conda environment and making only slight modifications to their existing command lines, without requiring wholesale changes to how they work.",
      "authors": {
        "Jas Kalayan": "https://orcid.org/0000-0002-6833-1864",
        "James Gebbie-Rayet": "https://orcid.org/0000-0001-8271-3431",
        "Harry Swift": "https://orcid.org/0009-0007-3323-753X"
      },
      "category": "data-tools",
      "image": "aiida-gromacs-logo.svg",
      "github": "https://github.com/CCPBioSim/aiida-gromacs",
      "docs": "https://aiida-gromacs.readthedocs.io",
      "pypi": true,
      "conda": true
    }
  }
}