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From biomolecular data to information - 2022 CCP5 Summer School, Durham

This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.

Instructors

Matteo Degiacomi
Micaela Matta
Antonia Mey

Location

Durham University
Room: W414

W414 is on the fourth floor of the Geography ("West") building. Enter at the northeast corner of the building at 54.767675, -1.573041. We've been asked not to use the "staff" toilets near W414, but rather to use the facilities on the ground floor. I shall be putting up some signage.

Schedule

DaySessionMaterials
26th PMIntroduction to the MDAnalysis package (Micaela Matta)MDA Part 1
26th PMMDAnalysis: advanced topics (Micaela Matta)MDA Part 2
27th AMDimensionality reduction, part 1 (Antonia Mey)Dimensionality reduction 1
27th AMDimensionality reduction, part 2 (Matteo Degiacomi)Dimensionality reduction 2
27th PMData clustering (Antonia Mey)Clustering
27th PMData classification (Matteo Degiacomi)Classification

Setting up your Python environment before the workshop

Instructions for setting up your environment to run this workshop locally are provided in INSTALL.md.

A full list of the required Python packages can be seen inside environment.yml.

As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!

Google Colab

If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.

Course pre-requisites

The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.

License

The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.

The MDAnalysis material is licences under CC-BY 4.0 Creative Commons Licence

The ML material is licenced under CC-BY-SA 4.0.

Creative Commons Licence

See here for the details of the licence

Acknowledgements

Please see AUTHORS.md for a list of contributors to the workshop materials.

About

No description or website provided.

Topics

workshop-materials

Resources

Readme
License

Code of conduct

Code of conduct
Activity
Custom properties

Stars

17 stars

Watchers

7 watching

Forks

5 forks
Report repository

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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From biomolecular data to information - 2022 CCP5 Summer School, Durham
This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.
Instructors
Matteo Degiacomi

Micaela Matta

Antonia Mey
Location
Durham University

Room: W414
W414 is on the fourth floor of the Geography ("West") building. Enter at
the northeast corner of the building at 54.767675, -1.573041. We've
been asked not to use the "staff" toilets near W414, but rather to use
the facilities on the ground floor. I shall be putting up some signage.
Schedule
DaySessionMaterials
26th PMIntroduction to the MDAnalysis package (Micaela Matta)MDA Part 1
26th PMMDAnalysis: advanced topics (Micaela Matta)MDA Part 2
27th AMDimensionality reduction, part 1 (Antonia Mey)Dimensionality reduction 1
27th AMDimensionality reduction, part 2 (Matteo Degiacomi)Dimensionality reduction 2
27th PMData clustering (Antonia Mey)Clustering
27th PMData classification (Matteo Degiacomi)Classification
Setting up your Python environment before the workshop
Instructions for setting up your environment to run this workshop locally
are provided in INSTALL.md.
A full list of the required Python packages can be seen inside environment.yml.
As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!
Google Colab
If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.
Course pre-requisites
The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.
License
The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.
The MDAnalysis material is licences under CC-BY 4.0
Creative Commons Licence
The ML material is licenced under CC-BY-SA 4.0.
Creative Commons Licence
See here for the details of the licence
Acknowledgements
Please see AUTHORS.md for a list of contributors to the workshop
materials.
About
No description or website provided.
Topics
workshop-materials
Resources
Readme
License
Code of conduct
Code of conduct
Activity
Custom properties
Stars
17 stars
Watchers
7 watching
Forks
5 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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From biomolecular data to information - 2022 CCP5 Summer School, Durham
This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.
Instructors
Matteo Degiacomi

Micaela Matta

Antonia Mey
Location
Durham University

Room: W414
W414 is on the fourth floor of the Geography ("West") building. Enter at
the northeast corner of the building at 54.767675, -1.573041. We've
been asked not to use the "staff" toilets near W414, but rather to use
the facilities on the ground floor. I shall be putting up some signage.
Schedule
DaySessionMaterials
26th PMIntroduction to the MDAnalysis package (Micaela Matta)MDA Part 1
26th PMMDAnalysis: advanced topics (Micaela Matta)MDA Part 2
27th AMDimensionality reduction, part 1 (Antonia Mey)Dimensionality reduction 1
27th AMDimensionality reduction, part 2 (Matteo Degiacomi)Dimensionality reduction 2
27th PMData clustering (Antonia Mey)Clustering
27th PMData classification (Matteo Degiacomi)Classification
Setting up your Python environment before the workshop
Instructions for setting up your environment to run this workshop locally
are provided in INSTALL.md.
A full list of the required Python packages can be seen inside environment.yml.
As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!
Google Colab
If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.
Course pre-requisites
The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.
License
The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.
The MDAnalysis material is licences under CC-BY 4.0
Creative Commons Licence
The ML material is licenced under CC-BY-SA 4.0.
Creative Commons Licence
See here for the details of the licence
Acknowledgements
Please see AUTHORS.md for a list of contributors to the workshop
materials.
About
No description or website provided.
Topics
workshop-materials
Resources
Readme
License
Code of conduct
Code of conduct
Activity
Custom properties
Stars
17 stars
Watchers
7 watching
Forks
5 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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From biomolecular data to information - 2022 CCP5 Summer School, Durham
This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.
Instructors
Matteo Degiacomi

Micaela Matta

Antonia Mey
Location
Durham University

Room: W414
W414 is on the fourth floor of the Geography ("West") building. Enter at
the northeast corner of the building at 54.767675, -1.573041. We've
been asked not to use the "staff" toilets near W414, but rather to use
the facilities on the ground floor. I shall be putting up some signage.
Schedule
DaySessionMaterials
26th PMIntroduction to the MDAnalysis package (Micaela Matta)MDA Part 1
26th PMMDAnalysis: advanced topics (Micaela Matta)MDA Part 2
27th AMDimensionality reduction, part 1 (Antonia Mey)Dimensionality reduction 1
27th AMDimensionality reduction, part 2 (Matteo Degiacomi)Dimensionality reduction 2
27th PMData clustering (Antonia Mey)Clustering
27th PMData classification (Matteo Degiacomi)Classification
Setting up your Python environment before the workshop
Instructions for setting up your environment to run this workshop locally
are provided in INSTALL.md.
A full list of the required Python packages can be seen inside environment.yml.
As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!
Google Colab
If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.
Course pre-requisites
The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.
License
The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.
The MDAnalysis material is licences under CC-BY 4.0
Creative Commons Licence
The ML material is licenced under CC-BY-SA 4.0.
Creative Commons Licence
See here for the details of the licence
Acknowledgements
Please see AUTHORS.md for a list of contributors to the workshop
materials.
About
No description or website provided.
Topics
workshop-materials
Resources
Readme
License
Code of conduct
Code of conduct
Activity
Custom properties
Stars
17 stars
Watchers
7 watching
Forks
5 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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From biomolecular data to information - 2022 CCP5 Summer School, Durham
This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.
Instructors
Matteo Degiacomi

Micaela Matta

Antonia Mey
Location
Durham University

Room: W414
W414 is on the fourth floor of the Geography ("West") building. Enter at
the northeast corner of the building at 54.767675, -1.573041. We've
been asked not to use the "staff" toilets near W414, but rather to use
the facilities on the ground floor. I shall be putting up some signage.
Schedule
DaySessionMaterials
26th PMIntroduction to the MDAnalysis package (Micaela Matta)MDA Part 1
26th PMMDAnalysis: advanced topics (Micaela Matta)MDA Part 2
27th AMDimensionality reduction, part 1 (Antonia Mey)Dimensionality reduction 1
27th AMDimensionality reduction, part 2 (Matteo Degiacomi)Dimensionality reduction 2
27th PMData clustering (Antonia Mey)Clustering
27th PMData classification (Matteo Degiacomi)Classification
Setting up your Python environment before the workshop
Instructions for setting up your environment to run this workshop locally
are provided in INSTALL.md.
A full list of the required Python packages can be seen inside environment.yml.
As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!
Google Colab
If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.
Course pre-requisites
The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.
License
The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.
The MDAnalysis material is licences under CC-BY 4.0
Creative Commons Licence
The ML material is licenced under CC-BY-SA 4.0.
Creative Commons Licence
See here for the details of the licence
Acknowledgements
Please see AUTHORS.md for a list of contributors to the workshop
materials.
About
No description or website provided.
Topics
workshop-materials
Resources
Readme
License
Code of conduct
Code of conduct
Activity
Custom properties
Stars
17 stars
Watchers
7 watching
Forks
5 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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From biomolecular data to information - 2022 CCP5 Summer School, Durham
This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.
Instructors
Matteo Degiacomi

Micaela Matta

Antonia Mey
Location
Durham University

Room: W414
W414 is on the fourth floor of the Geography ("West") building. Enter at
the northeast corner of the building at 54.767675, -1.573041. We've
been asked not to use the "staff" toilets near W414, but rather to use
the facilities on the ground floor. I shall be putting up some signage.
Schedule
DaySessionMaterials
26th PMIntroduction to the MDAnalysis package (Micaela Matta)MDA Part 1
26th PMMDAnalysis: advanced topics (Micaela Matta)MDA Part 2
27th AMDimensionality reduction, part 1 (Antonia Mey)Dimensionality reduction 1
27th AMDimensionality reduction, part 2 (Matteo Degiacomi)Dimensionality reduction 2
27th PMData clustering (Antonia Mey)Clustering
27th PMData classification (Matteo Degiacomi)Classification
Setting up your Python environment before the workshop
Instructions for setting up your environment to run this workshop locally
are provided in INSTALL.md.
A full list of the required Python packages can be seen inside environment.yml.
As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!
Google Colab
If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.
Course pre-requisites
The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.
License
The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.
The MDAnalysis material is licences under CC-BY 4.0
Creative Commons Licence
The ML material is licenced under CC-BY-SA 4.0.
Creative Commons Licence
See here for the details of the licence
Acknowledgements
Please see AUTHORS.md for a list of contributors to the workshop
materials.
About
No description or website provided.
Topics
workshop-materials
Resources
Readme
License
Code of conduct
Code of conduct
Activity
Custom properties
Stars
17 stars
Watchers
7 watching
Forks
5 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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From biomolecular data to information - 2022 CCP5 Summer School, Durham
This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.
Instructors
Matteo Degiacomi

Micaela Matta

Antonia Mey
Location
Durham University

Room: W414
W414 is on the fourth floor of the Geography ("West") building. Enter at
the northeast corner of the building at 54.767675, -1.573041. We've
been asked not to use the "staff" toilets near W414, but rather to use
the facilities on the ground floor. I shall be putting up some signage.
Schedule
DaySessionMaterials
26th PMIntroduction to the MDAnalysis package (Micaela Matta)MDA Part 1
26th PMMDAnalysis: advanced topics (Micaela Matta)MDA Part 2
27th AMDimensionality reduction, part 1 (Antonia Mey)Dimensionality reduction 1
27th AMDimensionality reduction, part 2 (Matteo Degiacomi)Dimensionality reduction 2
27th PMData clustering (Antonia Mey)Clustering
27th PMData classification (Matteo Degiacomi)Classification
Setting up your Python environment before the workshop
Instructions for setting up your environment to run this workshop locally
are provided in INSTALL.md.
A full list of the required Python packages can be seen inside environment.yml.
As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!
Google Colab
If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.
Course pre-requisites
The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.
License
The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.
The MDAnalysis material is licences under CC-BY 4.0
Creative Commons Licence
The ML material is licenced under CC-BY-SA 4.0.
Creative Commons Licence
See here for the details of the licence
Acknowledgements
Please see AUTHORS.md for a list of contributors to the workshop
materials.
About
No description or website provided.
Topics
workshop-materials
Resources
Readme
License
Code of conduct
Code of conduct
Activity
Custom properties
Stars
17 stars
Watchers
7 watching
Forks
5 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
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From biomolecular data to information - 2022 CCP5 Summer School, Durham
This repository contains all the materials for the MDAnalysis/Machine Learning tutorials that form part of the CCP5 Biomolecular Simulation Advance Course taking place on July 26-27th at Durham University.
Instructors
Matteo Degiacomi

Micaela Matta

Antonia Mey
Location
Durham University

Room: W414
W414 is on the fourth floor of the Geography ("West") building. Enter at
the northeast corner of the building at 54.767675, -1.573041. We've
been asked not to use the "staff" toilets near W414, but rather to use
the facilities on the ground floor. I shall be putting up some signage.
Schedule
DaySessionMaterials
26th PMIntroduction to the MDAnalysis package (Micaela Matta)MDA Part 1
26th PMMDAnalysis: advanced topics (Micaela Matta)MDA Part 2
27th AMDimensionality reduction, part 1 (Antonia Mey)Dimensionality reduction 1
27th AMDimensionality reduction, part 2 (Matteo Degiacomi)Dimensionality reduction 2
27th PMData clustering (Antonia Mey)Clustering
27th PMData classification (Matteo Degiacomi)Classification
Setting up your Python environment before the workshop
Instructions for setting up your environment to run this workshop locally
are provided in INSTALL.md.
A full list of the required Python packages can be seen inside environment.yml.
As downloading and installing everything will take a little while, ideally you should follow these steps before the workshop starts. If you encounter any issues during installation, we can help!
Google Colab
If for any reason you cannot set up a local environment with all required packages, you can use Google Colab to run all workshop notebooks directly from your browser, no installation required.
Course pre-requisites
The course assumes that attendees have a working knowledge of Jupyter notebooks, Python (especially the NumPy library), and the bash shell.
License
The MDAnalysis logo and its derivatives are licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.
The MDAnalysis material is licences under CC-BY 4.0
Creative Commons Licence
The ML material is licenced under CC-BY-SA 4.0.
Creative Commons Licence
See here for the details of the licence
Acknowledgements
Please see AUTHORS.md for a list of contributors to the workshop
materials.
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