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SubNetX

The data and scripts contained in this repository allow the user to generate novel pathways predicitons for any of the compounds available in the network.

Installation

The installation can be completed in less than 10 minutes, including installation of dependencies and fetching the data from the git repository.

Requirements

  • python 3
  • rdkit environment
  • networkx

rdkit is required for balance calculation and visualisation.

Please, install rdkit and use rdkit environment for running SubNetX. First install anaconda: https://docs.anaconda.com/anaconda/install/index.html

Then install rdkit as described here: https://www.rdkit.org/docs/Install.html.

$ conda create -c conda-forge -n my-rdkit-env rdkit$ conda activate my-rdkit-env

Since networkx package is not part of the default rdkit environment, install it to the environment as follows when the environment is activated:

$ conda install networkx

Download repository

$ git clone https://github.com/EPFL-LCSB/SubNetX.git

If you are installing on macOS, make sure you have Homebrew installed, otherwise you might get "git: 'lfs' is not a git command." error. Once you installed Homebrew, run

$ brew install git-lfs$ run git-lfs install

Note

Data files are stored using git large file storage (lfs). The make file will install git lfs automatically. However, if lfs was not installed previously, the repository has to be updated after installation:

$ git-lfs pull

This is needed to retrieve the data files from the repository after installation.

The default data used in SubNetX is ARBRE repository data (https://doi.org/10.1016/j.ymben.2022.03.013)

Test

Ex. ajmalicine, can be repeated for any other compound

  • copy a test project folder from SubNetX/1_subnetwork_extraction/tutorials/any_mode_of_tutorial/ajmalicine to SubNetX/1_subnetwork_extraction/projects/ajmalicine

Run the code as following

$ cd SubNetX/1_subnetwork_extraction/code

$ python3 Main.py ajmalicine

Usage

  • create a folder with the name of your project in the "projects" directory (e.g. .../SubNetX/1_subnetwork_extraction/projects/your_compound)
  • copy the parameters file from the .../1_subnetwork_extraction/defaults folder to your project folder
  • follow the instructions for the parameters.txt adjustment specified in the parameters file (for more details consult the manuscript)

Network expansion

  • Set target compound as LCSB ID of compound (e.g., 1467874237, can be found in data/ARBRE/compounds.csv, cUID column)
  • The minimal amount of adjustments for your search is substituting the target ID by your target ID.

You will get the following output:

  • output_optimization_input: folder that should be passed to the optimisation stage of the algorithm
  • stats: number of compounds and network statistics at the different stages of subnetwork extraction
  • auxilary_output: detailed overview of boundaries at each stage and initial pathways
  • figures: view of the extracted subnetwork

The .gdf files ready for visualisation in Gephi software are available at arbre/output/{projectname}/visualization/gephifiles

The generation is represented by the color and is labeled in the edges part of the .gdf file in "color VARCHAR" column.

You can install Gephi from https://gephi.org.

Finishing work with SubNetX

Deactivate your rdkit environment as follows:

$ conda deactivate

About

No description, website, or topics provided.

Resources

Readme
MIT license
Activity
Custom properties

Stars

8 stars

Watchers

1 watching

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1 fork
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
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})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Repository files navigation
SubNetX
The data and scripts contained in this repository allow the user to generate novel
pathways predicitons for any of the compounds available in the network.
Installation
The installation can be completed in less than 10 minutes, including installation of
dependencies and fetching the data from the git repository.
Requirements
  • python 3
  • rdkit environment
  • networkx
rdkit is required for balance calculation and visualisation.
Please, install rdkit and use rdkit environment for running SubNetX.
First install anaconda: https://docs.anaconda.com/anaconda/install/index.html
Then install rdkit as described here: https://www.rdkit.org/docs/Install.html.
$ conda create -c conda-forge -n my-rdkit-env rdkit$ conda activate my-rdkit-env
Since networkx package is not part of the default rdkit environment, install it to the environment as follows when the environment is activated:
$ conda install networkx
Download repository
$ git clone https://github.com/EPFL-LCSB/SubNetX.git
If you are installing on macOS, make sure you have Homebrew installed, otherwise you might get "git: 'lfs' is not a git command." error.
Once you installed Homebrew, run
$ brew install git-lfs$ run git-lfs install
Note
Data files are stored using git large file storage (lfs). The make file will install git lfs
automatically. However, if lfs was not installed previously, the repository has to be
updated after installation:
$ git-lfs pull
This is needed to retrieve the data files from the repository after installation.
The default data used in SubNetX is ARBRE repository data (https://doi.org/10.1016/j.ymben.2022.03.013)
Test
Ex. ajmalicine, can be repeated for any other compound
  • copy a test project folder from SubNetX/1_subnetwork_extraction/tutorials/any_mode_of_tutorial/ajmalicine to SubNetX/1_subnetwork_extraction/projects/ajmalicine
Run the code as following
$ cd SubNetX/1_subnetwork_extraction/code
$ python3 Main.py ajmalicine
Usage
  • create a folder with the name of your project in the "projects" directory (e.g. .../SubNetX/1_subnetwork_extraction/projects/your_compound)
  • copy the parameters file from the .../1_subnetwork_extraction/defaults folder to your project folder
  • follow the instructions for the parameters.txt adjustment specified in the parameters file (for more details consult the manuscript)
Network expansion
  • Set target compound as LCSB ID of compound (e.g., 1467874237, can be found in data/ARBRE/compounds.csv, cUID column)
  • The minimal amount of adjustments for your search is substituting the target ID by your target ID.
You will get the following output:
  • output_optimization_input: folder that should be passed to the optimisation stage of the algorithm
  • stats: number of compounds and network statistics at the different stages of subnetwork extraction
  • auxilary_output: detailed overview of boundaries at each stage and initial pathways
  • figures: view of the extracted subnetwork
The .gdf files ready for visualisation in Gephi software are available at arbre/output/{projectname}/visualization/gephifiles
The generation is represented by the color and is labeled in the edges part of the .gdf file in "color VARCHAR" column.
You can install Gephi from https://gephi.org.
Finishing work with SubNetX
Deactivate your rdkit environment as follows:
$ conda deactivate
About
No description, website, or topics provided.
Resources
Readme
MIT license
Activity
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Stars
8 stars
Watchers
1 watching
Forks
1 fork
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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} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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readme.pdf
readme.pdf
Repository files navigation
SubNetX
The data and scripts contained in this repository allow the user to generate novel
pathways predicitons for any of the compounds available in the network.
Installation
The installation can be completed in less than 10 minutes, including installation of
dependencies and fetching the data from the git repository.
Requirements
  • python 3
  • rdkit environment
  • networkx
rdkit is required for balance calculation and visualisation.
Please, install rdkit and use rdkit environment for running SubNetX.
First install anaconda: https://docs.anaconda.com/anaconda/install/index.html
Then install rdkit as described here: https://www.rdkit.org/docs/Install.html.
$ conda create -c conda-forge -n my-rdkit-env rdkit$ conda activate my-rdkit-env
Since networkx package is not part of the default rdkit environment, install it to the environment as follows when the environment is activated:
$ conda install networkx
Download repository
$ git clone https://github.com/EPFL-LCSB/SubNetX.git
If you are installing on macOS, make sure you have Homebrew installed, otherwise you might get "git: 'lfs' is not a git command." error.
Once you installed Homebrew, run
$ brew install git-lfs$ run git-lfs install
Note
Data files are stored using git large file storage (lfs). The make file will install git lfs
automatically. However, if lfs was not installed previously, the repository has to be
updated after installation:
$ git-lfs pull
This is needed to retrieve the data files from the repository after installation.
The default data used in SubNetX is ARBRE repository data (https://doi.org/10.1016/j.ymben.2022.03.013)
Test
Ex. ajmalicine, can be repeated for any other compound
  • copy a test project folder from SubNetX/1_subnetwork_extraction/tutorials/any_mode_of_tutorial/ajmalicine to SubNetX/1_subnetwork_extraction/projects/ajmalicine
Run the code as following
$ cd SubNetX/1_subnetwork_extraction/code
$ python3 Main.py ajmalicine
Usage
  • create a folder with the name of your project in the "projects" directory (e.g. .../SubNetX/1_subnetwork_extraction/projects/your_compound)
  • copy the parameters file from the .../1_subnetwork_extraction/defaults folder to your project folder
  • follow the instructions for the parameters.txt adjustment specified in the parameters file (for more details consult the manuscript)
Network expansion
  • Set target compound as LCSB ID of compound (e.g., 1467874237, can be found in data/ARBRE/compounds.csv, cUID column)
  • The minimal amount of adjustments for your search is substituting the target ID by your target ID.
You will get the following output:
  • output_optimization_input: folder that should be passed to the optimisation stage of the algorithm
  • stats: number of compounds and network statistics at the different stages of subnetwork extraction
  • auxilary_output: detailed overview of boundaries at each stage and initial pathways
  • figures: view of the extracted subnetwork
The .gdf files ready for visualisation in Gephi software are available at arbre/output/{projectname}/visualization/gephifiles
The generation is represented by the color and is labeled in the edges part of the .gdf file in "color VARCHAR" column.
You can install Gephi from https://gephi.org.
Finishing work with SubNetX
Deactivate your rdkit environment as follows:
$ conda deactivate
About
No description, website, or topics provided.
Resources
Readme
MIT license
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Stars
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1 watching
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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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Repository files navigation
SubNetX
The data and scripts contained in this repository allow the user to generate novel
pathways predicitons for any of the compounds available in the network.
Installation
The installation can be completed in less than 10 minutes, including installation of
dependencies and fetching the data from the git repository.
Requirements
  • python 3
  • rdkit environment
  • networkx
rdkit is required for balance calculation and visualisation.
Please, install rdkit and use rdkit environment for running SubNetX.
First install anaconda: https://docs.anaconda.com/anaconda/install/index.html
Then install rdkit as described here: https://www.rdkit.org/docs/Install.html.
$ conda create -c conda-forge -n my-rdkit-env rdkit$ conda activate my-rdkit-env
Since networkx package is not part of the default rdkit environment, install it to the environment as follows when the environment is activated:
$ conda install networkx
Download repository
$ git clone https://github.com/EPFL-LCSB/SubNetX.git
If you are installing on macOS, make sure you have Homebrew installed, otherwise you might get "git: 'lfs' is not a git command." error.
Once you installed Homebrew, run
$ brew install git-lfs$ run git-lfs install
Note
Data files are stored using git large file storage (lfs). The make file will install git lfs
automatically. However, if lfs was not installed previously, the repository has to be
updated after installation:
$ git-lfs pull
This is needed to retrieve the data files from the repository after installation.
The default data used in SubNetX is ARBRE repository data (https://doi.org/10.1016/j.ymben.2022.03.013)
Test
Ex. ajmalicine, can be repeated for any other compound
  • copy a test project folder from SubNetX/1_subnetwork_extraction/tutorials/any_mode_of_tutorial/ajmalicine to SubNetX/1_subnetwork_extraction/projects/ajmalicine
Run the code as following
$ cd SubNetX/1_subnetwork_extraction/code
$ python3 Main.py ajmalicine
Usage
  • create a folder with the name of your project in the "projects" directory (e.g. .../SubNetX/1_subnetwork_extraction/projects/your_compound)
  • copy the parameters file from the .../1_subnetwork_extraction/defaults folder to your project folder
  • follow the instructions for the parameters.txt adjustment specified in the parameters file (for more details consult the manuscript)
Network expansion
  • Set target compound as LCSB ID of compound (e.g., 1467874237, can be found in data/ARBRE/compounds.csv, cUID column)
  • The minimal amount of adjustments for your search is substituting the target ID by your target ID.
You will get the following output:
  • output_optimization_input: folder that should be passed to the optimisation stage of the algorithm
  • stats: number of compounds and network statistics at the different stages of subnetwork extraction
  • auxilary_output: detailed overview of boundaries at each stage and initial pathways
  • figures: view of the extracted subnetwork
The .gdf files ready for visualisation in Gephi software are available at arbre/output/{projectname}/visualization/gephifiles
The generation is represented by the color and is labeled in the edges part of the .gdf file in "color VARCHAR" column.
You can install Gephi from https://gephi.org.
Finishing work with SubNetX
Deactivate your rdkit environment as follows:
$ conda deactivate
About
No description, website, or topics provided.
Resources
Readme
MIT license
Activity
Custom properties
Stars
8 stars
Watchers
1 watching
Forks
1 fork
Report repository
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, '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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Repository files navigation
SubNetX
The data and scripts contained in this repository allow the user to generate novel
pathways predicitons for any of the compounds available in the network.
Installation
The installation can be completed in less than 10 minutes, including installation of
dependencies and fetching the data from the git repository.
Requirements
  • python 3
  • rdkit environment
  • networkx
rdkit is required for balance calculation and visualisation.
Please, install rdkit and use rdkit environment for running SubNetX.
First install anaconda: https://docs.anaconda.com/anaconda/install/index.html
Then install rdkit as described here: https://www.rdkit.org/docs/Install.html.
$ conda create -c conda-forge -n my-rdkit-env rdkit$ conda activate my-rdkit-env
Since networkx package is not part of the default rdkit environment, install it to the environment as follows when the environment is activated:
$ conda install networkx
Download repository
$ git clone https://github.com/EPFL-LCSB/SubNetX.git
If you are installing on macOS, make sure you have Homebrew installed, otherwise you might get "git: 'lfs' is not a git command." error.
Once you installed Homebrew, run
$ brew install git-lfs$ run git-lfs install
Note
Data files are stored using git large file storage (lfs). The make file will install git lfs
automatically. However, if lfs was not installed previously, the repository has to be
updated after installation:
$ git-lfs pull
This is needed to retrieve the data files from the repository after installation.
The default data used in SubNetX is ARBRE repository data (https://doi.org/10.1016/j.ymben.2022.03.013)
Test
Ex. ajmalicine, can be repeated for any other compound
  • copy a test project folder from SubNetX/1_subnetwork_extraction/tutorials/any_mode_of_tutorial/ajmalicine to SubNetX/1_subnetwork_extraction/projects/ajmalicine
Run the code as following
$ cd SubNetX/1_subnetwork_extraction/code
$ python3 Main.py ajmalicine
Usage
  • create a folder with the name of your project in the "projects" directory (e.g. .../SubNetX/1_subnetwork_extraction/projects/your_compound)
  • copy the parameters file from the .../1_subnetwork_extraction/defaults folder to your project folder
  • follow the instructions for the parameters.txt adjustment specified in the parameters file (for more details consult the manuscript)
Network expansion
  • Set target compound as LCSB ID of compound (e.g., 1467874237, can be found in data/ARBRE/compounds.csv, cUID column)
  • The minimal amount of adjustments for your search is substituting the target ID by your target ID.
You will get the following output:
  • output_optimization_input: folder that should be passed to the optimisation stage of the algorithm
  • stats: number of compounds and network statistics at the different stages of subnetwork extraction
  • auxilary_output: detailed overview of boundaries at each stage and initial pathways
  • figures: view of the extracted subnetwork
The .gdf files ready for visualisation in Gephi software are available at arbre/output/{projectname}/visualization/gephifiles
The generation is represented by the color and is labeled in the edges part of the .gdf file in "color VARCHAR" column.
You can install Gephi from https://gephi.org.
Finishing work with SubNetX
Deactivate your rdkit environment as follows:
$ conda deactivate
About
No description, website, or topics provided.
Resources
Readme
MIT license
Activity
Custom properties
Stars
8 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors
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, '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); }
})();
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Repository files navigation
SubNetX
The data and scripts contained in this repository allow the user to generate novel
pathways predicitons for any of the compounds available in the network.
Installation
The installation can be completed in less than 10 minutes, including installation of
dependencies and fetching the data from the git repository.
Requirements
  • python 3
  • rdkit environment
  • networkx
rdkit is required for balance calculation and visualisation.
Please, install rdkit and use rdkit environment for running SubNetX.
First install anaconda: https://docs.anaconda.com/anaconda/install/index.html
Then install rdkit as described here: https://www.rdkit.org/docs/Install.html.
$ conda create -c conda-forge -n my-rdkit-env rdkit$ conda activate my-rdkit-env
Since networkx package is not part of the default rdkit environment, install it to the environment as follows when the environment is activated:
$ conda install networkx
Download repository
$ git clone https://github.com/EPFL-LCSB/SubNetX.git
If you are installing on macOS, make sure you have Homebrew installed, otherwise you might get "git: 'lfs' is not a git command." error.
Once you installed Homebrew, run
$ brew install git-lfs$ run git-lfs install
Note
Data files are stored using git large file storage (lfs). The make file will install git lfs
automatically. However, if lfs was not installed previously, the repository has to be
updated after installation:
$ git-lfs pull
This is needed to retrieve the data files from the repository after installation.
The default data used in SubNetX is ARBRE repository data (https://doi.org/10.1016/j.ymben.2022.03.013)
Test
Ex. ajmalicine, can be repeated for any other compound
  • copy a test project folder from SubNetX/1_subnetwork_extraction/tutorials/any_mode_of_tutorial/ajmalicine to SubNetX/1_subnetwork_extraction/projects/ajmalicine
Run the code as following
$ cd SubNetX/1_subnetwork_extraction/code
$ python3 Main.py ajmalicine
Usage
  • create a folder with the name of your project in the "projects" directory (e.g. .../SubNetX/1_subnetwork_extraction/projects/your_compound)
  • copy the parameters file from the .../1_subnetwork_extraction/defaults folder to your project folder
  • follow the instructions for the parameters.txt adjustment specified in the parameters file (for more details consult the manuscript)
Network expansion
  • Set target compound as LCSB ID of compound (e.g., 1467874237, can be found in data/ARBRE/compounds.csv, cUID column)
  • The minimal amount of adjustments for your search is substituting the target ID by your target ID.
You will get the following output:
  • output_optimization_input: folder that should be passed to the optimisation stage of the algorithm
  • stats: number of compounds and network statistics at the different stages of subnetwork extraction
  • auxilary_output: detailed overview of boundaries at each stage and initial pathways
  • figures: view of the extracted subnetwork
The .gdf files ready for visualisation in Gephi software are available at arbre/output/{projectname}/visualization/gephifiles
The generation is represented by the color and is labeled in the edges part of the .gdf file in "color VARCHAR" column.
You can install Gephi from https://gephi.org.
Finishing work with SubNetX
Deactivate your rdkit environment as follows:
$ conda deactivate
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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");
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} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
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var __m = "*";
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Repository files navigation
SubNetX
The data and scripts contained in this repository allow the user to generate novel
pathways predicitons for any of the compounds available in the network.
Installation
The installation can be completed in less than 10 minutes, including installation of
dependencies and fetching the data from the git repository.
Requirements
  • python 3
  • rdkit environment
  • networkx
rdkit is required for balance calculation and visualisation.
Please, install rdkit and use rdkit environment for running SubNetX.
First install anaconda: https://docs.anaconda.com/anaconda/install/index.html
Then install rdkit as described here: https://www.rdkit.org/docs/Install.html.
$ conda create -c conda-forge -n my-rdkit-env rdkit$ conda activate my-rdkit-env
Since networkx package is not part of the default rdkit environment, install it to the environment as follows when the environment is activated:
$ conda install networkx
Download repository
$ git clone https://github.com/EPFL-LCSB/SubNetX.git
If you are installing on macOS, make sure you have Homebrew installed, otherwise you might get "git: 'lfs' is not a git command." error.
Once you installed Homebrew, run
$ brew install git-lfs$ run git-lfs install
Note
Data files are stored using git large file storage (lfs). The make file will install git lfs
automatically. However, if lfs was not installed previously, the repository has to be
updated after installation:
$ git-lfs pull
This is needed to retrieve the data files from the repository after installation.
The default data used in SubNetX is ARBRE repository data (https://doi.org/10.1016/j.ymben.2022.03.013)
Test
Ex. ajmalicine, can be repeated for any other compound
  • copy a test project folder from SubNetX/1_subnetwork_extraction/tutorials/any_mode_of_tutorial/ajmalicine to SubNetX/1_subnetwork_extraction/projects/ajmalicine
Run the code as following
$ cd SubNetX/1_subnetwork_extraction/code
$ python3 Main.py ajmalicine
Usage
  • create a folder with the name of your project in the "projects" directory (e.g. .../SubNetX/1_subnetwork_extraction/projects/your_compound)
  • copy the parameters file from the .../1_subnetwork_extraction/defaults folder to your project folder
  • follow the instructions for the parameters.txt adjustment specified in the parameters file (for more details consult the manuscript)
Network expansion
  • Set target compound as LCSB ID of compound (e.g., 1467874237, can be found in data/ARBRE/compounds.csv, cUID column)
  • The minimal amount of adjustments for your search is substituting the target ID by your target ID.
You will get the following output:
  • output_optimization_input: folder that should be passed to the optimisation stage of the algorithm
  • stats: number of compounds and network statistics at the different stages of subnetwork extraction
  • auxilary_output: detailed overview of boundaries at each stage and initial pathways
  • figures: view of the extracted subnetwork
The .gdf files ready for visualisation in Gephi software are available at arbre/output/{projectname}/visualization/gephifiles
The generation is represented by the color and is labeled in the edges part of the .gdf file in "color VARCHAR" column.
You can install Gephi from https://gephi.org.
Finishing work with SubNetX
Deactivate your rdkit environment as follows:
$ conda deactivate
About
No description, website, or topics provided.
Resources
Readme
MIT license
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Stars
8 stars
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1 watching
Forks
1 fork
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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README.md
readme.pdf
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Repository files navigation
SubNetX
The data and scripts contained in this repository allow the user to generate novel
pathways predicitons for any of the compounds available in the network.
Installation
The installation can be completed in less than 10 minutes, including installation of
dependencies and fetching the data from the git repository.
Requirements
  • python 3
  • rdkit environment
  • networkx
rdkit is required for balance calculation and visualisation.
Please, install rdkit and use rdkit environment for running SubNetX.
First install anaconda: https://docs.anaconda.com/anaconda/install/index.html
Then install rdkit as described here: https://www.rdkit.org/docs/Install.html.
$ conda create -c conda-forge -n my-rdkit-env rdkit$ conda activate my-rdkit-env
Since networkx package is not part of the default rdkit environment, install it to the environment as follows when the environment is activated:
$ conda install networkx
Download repository
$ git clone https://github.com/EPFL-LCSB/SubNetX.git
If you are installing on macOS, make sure you have Homebrew installed, otherwise you might get "git: 'lfs' is not a git command." error.
Once you installed Homebrew, run
$ brew install git-lfs$ run git-lfs install
Note
Data files are stored using git large file storage (lfs). The make file will install git lfs
automatically. However, if lfs was not installed previously, the repository has to be
updated after installation:
$ git-lfs pull
This is needed to retrieve the data files from the repository after installation.
The default data used in SubNetX is ARBRE repository data (https://doi.org/10.1016/j.ymben.2022.03.013)
Test
Ex. ajmalicine, can be repeated for any other compound
  • copy a test project folder from SubNetX/1_subnetwork_extraction/tutorials/any_mode_of_tutorial/ajmalicine to SubNetX/1_subnetwork_extraction/projects/ajmalicine
Run the code as following
$ cd SubNetX/1_subnetwork_extraction/code
$ python3 Main.py ajmalicine
Usage
  • create a folder with the name of your project in the "projects" directory (e.g. .../SubNetX/1_subnetwork_extraction/projects/your_compound)
  • copy the parameters file from the .../1_subnetwork_extraction/defaults folder to your project folder
  • follow the instructions for the parameters.txt adjustment specified in the parameters file (for more details consult the manuscript)
Network expansion
  • Set target compound as LCSB ID of compound (e.g., 1467874237, can be found in data/ARBRE/compounds.csv, cUID column)
  • The minimal amount of adjustments for your search is substituting the target ID by your target ID.
You will get the following output:
  • output_optimization_input: folder that should be passed to the optimisation stage of the algorithm
  • stats: number of compounds and network statistics at the different stages of subnetwork extraction
  • auxilary_output: detailed overview of boundaries at each stage and initial pathways
  • figures: view of the extracted subnetwork
The .gdf files ready for visualisation in Gephi software are available at arbre/output/{projectname}/visualization/gephifiles
The generation is represented by the color and is labeled in the edges part of the .gdf file in "color VARCHAR" column.
You can install Gephi from https://gephi.org.
Finishing work with SubNetX
Deactivate your rdkit environment as follows:
$ conda deactivate
About
No description, website, or topics provided.
Resources
Readme
MIT license
Activity
Custom properties
Stars
8 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors
Languages