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Project for the translation of SBML files into BNGL files. You can find more information about the project here.

Build StatusBuild status

Download Latest Test Builds

These builds are the from the head of master and are not guaranteed to be stable. Use at your own risk.

Requirements

You should use Python 3.5 or later. A number of Python libraries need to be installed, but these can be automatically installed in a Python virtual environment, which is exactly what the makefile does under Linux and OSX or what the PowerShell script does for Windows.

Ubuntu

sudo apt-get install -y python3-dev
sudo apt-get install -y python3-venv

Windows 10

You'll need to install Python 3. We recommend using Anaconda for this.

Optional for Developers

If you want to run ./atomizer/SBMLparser/sbmlTranslator.py directly, you can install all the Python requirements at the system level by doing:

cd SBMLparser
sudo pip3 install -r requirements.txt

Alternatively, you can do this at the user level:

cd SBMLparser
pip3 install --user -r requirements.txt

Installation

OSX and Linux

From the top-level directory, type the following:

make; make install

This will create an sbmlTranslator binary in ./atomizer/bin. This is made using PyInstaller.

Installation for Windows

Right click on ./atomizer/build_sbmlTranslator_win.ps1 and select Run with PowerShell.

Execution

./sbmlTranslator -i /path/to/sbml/file [-a] [-o output.bngl]

Optional arguments

  • [-a] activates the atomizer. Otherwise only a flat translation will be provided (no molecular structure)
  • [-p] activates pathway commons querying. An internet connection is required
  • [-b <path/to/bionetgen>] Enables post atomization analysis.
  • See [-h] for a full list of arguments

Directory Structure:

  • SBMLparser: Directory containing the main project.

    • sbmlTranslator.py: Entry level file

    • atomizer: Contains the main implicit assumption extraction code

      • analyzeSBML.py: lexical analysis engine
      • detectOntology.py: helper file for the lexical analysis engine (levenshtein distance, convention discovery, etc.)
      • analyzeRDF.py: extracts annotation information and gets it into the atomizer data model
      • resolveSCT.py: Creates the species composition table using lexical analysis, annotation information and the stoichiometry matrix
      • moleculeCreation.py: Creates the structured molecules for use in graph-creation

    • utils: contains several utility scripts used during the atomization process

      • consoleCommands.py: Interfaces with the BioNetGen console
      • pathwaysCommons.py: Queries BioGrid and pathways commons given an RDF annotation entry
  • stats: Extracts statistics of a set of atomized BioModels files

About

RNM to RBM translation project.

ruleworld.github.io/atomizer/

Resources

Readme
Activity
Custom properties

Stars

3 stars

Watchers

19 watching

Forks

4 forks
Report repository

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Packages

Used by

Contributors

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var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
GitHub - RuleWorld/atomizer: RNM to RBM translation project. · GitHub
Skip to content
BranchesTags
Repository files navigation
Project for the translation of SBML files into BNGL files. You can find more
information about the project here.
Build StatusBuild status
Download Latest Test Builds
These builds are the from the head of master and are not guaranteed to be
stable. Use at your own risk.
Requirements
You should use Python 3.5 or later. A number of Python libraries need to be
installed, but these can be automatically installed in a Python virtual
environment, which is exactly what the makefile does under Linux and OSX or
what the PowerShell script does for Windows.
Ubuntu
sudo apt-get install -y python3-dev
sudo apt-get install -y python3-venv

Windows 10
You'll need to install Python 3. We recommend using Anaconda for this.
Optional for Developers
If you want to run ./atomizer/SBMLparser/sbmlTranslator.py directly, you can
install all the Python requirements at the system level by doing:
cd SBMLparser
sudo pip3 install -r requirements.txt

Alternatively, you can do this at the user level:
cd SBMLparser
pip3 install --user -r requirements.txt

Installation
OSX and Linux
From the top-level directory, type the following:
make; make install

This will create an sbmlTranslator binary in ./atomizer/bin. This is made
using PyInstaller.
Installation for Windows
Right click on ./atomizer/build_sbmlTranslator_win.ps1 and select Run with PowerShell.
Execution
./sbmlTranslator -i /path/to/sbml/file [-a] [-o output.bngl]

Optional arguments
  • [-a] activates the atomizer. Otherwise only a flat translation will be provided (no molecular structure)
  • [-p] activates pathway commons querying. An internet connection is required
  • [-b <path/to/bionetgen>] Enables post atomization analysis.
  • See [-h] for a full list of arguments
Directory Structure:
  • SBMLparser: Directory containing the main project.

    • sbmlTranslator.py: Entry level file
    • atomizer: Contains the main implicit assumption extraction code
      • analyzeSBML.py: lexical analysis engine
      • detectOntology.py: helper file for the lexical analysis engine
(levenshtein distance, convention discovery, etc.)
      • analyzeRDF.py: extracts annotation information and gets it into the
atomizer data model
      • resolveSCT.py: Creates the species composition table using lexical
analysis, annotation information and the stoichiometry matrix
      • moleculeCreation.py: Creates the structured molecules for use in
graph-creation
    • utils: contains several utility scripts used during the atomization process
      • consoleCommands.py: Interfaces with the BioNetGen console
      • pathwaysCommons.py: Queries BioGrid and pathways commons given an RDF annotation entry
  • stats: Extracts statistics of a set of atomized BioModels files
About
RNM to RBM translation project. 
ruleworld.github.io/atomizer/
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
19 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
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var style = document.createElement('style');
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - RuleWorld/atomizer: RNM to RBM translation project. · GitHub
Skip to content
BranchesTags
Repository files navigation
Project for the translation of SBML files into BNGL files. You can find more
information about the project here.
Build StatusBuild status
Download Latest Test Builds
These builds are the from the head of master and are not guaranteed to be
stable. Use at your own risk.
Requirements
You should use Python 3.5 or later. A number of Python libraries need to be
installed, but these can be automatically installed in a Python virtual
environment, which is exactly what the makefile does under Linux and OSX or
what the PowerShell script does for Windows.
Ubuntu
sudo apt-get install -y python3-dev
sudo apt-get install -y python3-venv

Windows 10
You'll need to install Python 3. We recommend using Anaconda for this.
Optional for Developers
If you want to run ./atomizer/SBMLparser/sbmlTranslator.py directly, you can
install all the Python requirements at the system level by doing:
cd SBMLparser
sudo pip3 install -r requirements.txt

Alternatively, you can do this at the user level:
cd SBMLparser
pip3 install --user -r requirements.txt

Installation
OSX and Linux
From the top-level directory, type the following:
make; make install

This will create an sbmlTranslator binary in ./atomizer/bin. This is made
using PyInstaller.
Installation for Windows
Right click on ./atomizer/build_sbmlTranslator_win.ps1 and select Run with PowerShell.
Execution
./sbmlTranslator -i /path/to/sbml/file [-a] [-o output.bngl]

Optional arguments
  • [-a] activates the atomizer. Otherwise only a flat translation will be provided (no molecular structure)
  • [-p] activates pathway commons querying. An internet connection is required
  • [-b <path/to/bionetgen>] Enables post atomization analysis.
  • See [-h] for a full list of arguments
Directory Structure:
  • SBMLparser: Directory containing the main project.

    • sbmlTranslator.py: Entry level file
    • atomizer: Contains the main implicit assumption extraction code
      • analyzeSBML.py: lexical analysis engine
      • detectOntology.py: helper file for the lexical analysis engine
(levenshtein distance, convention discovery, etc.)
      • analyzeRDF.py: extracts annotation information and gets it into the
atomizer data model
      • resolveSCT.py: Creates the species composition table using lexical
analysis, annotation information and the stoichiometry matrix
      • moleculeCreation.py: Creates the structured molecules for use in
graph-creation
    • utils: contains several utility scripts used during the atomization process
      • consoleCommands.py: Interfaces with the BioNetGen console
      • pathwaysCommons.py: Queries BioGrid and pathways commons given an RDF annotation entry
  • stats: Extracts statistics of a set of atomized BioModels files
About
RNM to RBM translation project. 
ruleworld.github.io/atomizer/
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
19 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
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var ref = document.referrer;
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var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
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var found = false;
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mutations.forEach(function(m) {
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observer.observe(document.body, { childList: true, subtree: true });
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}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - RuleWorld/atomizer: RNM to RBM translation project. · GitHub
Skip to content
BranchesTags
Repository files navigation
Project for the translation of SBML files into BNGL files. You can find more
information about the project here.
Build StatusBuild status
Download Latest Test Builds
These builds are the from the head of master and are not guaranteed to be
stable. Use at your own risk.
Requirements
You should use Python 3.5 or later. A number of Python libraries need to be
installed, but these can be automatically installed in a Python virtual
environment, which is exactly what the makefile does under Linux and OSX or
what the PowerShell script does for Windows.
Ubuntu
sudo apt-get install -y python3-dev
sudo apt-get install -y python3-venv

Windows 10
You'll need to install Python 3. We recommend using Anaconda for this.
Optional for Developers
If you want to run ./atomizer/SBMLparser/sbmlTranslator.py directly, you can
install all the Python requirements at the system level by doing:
cd SBMLparser
sudo pip3 install -r requirements.txt

Alternatively, you can do this at the user level:
cd SBMLparser
pip3 install --user -r requirements.txt

Installation
OSX and Linux
From the top-level directory, type the following:
make; make install

This will create an sbmlTranslator binary in ./atomizer/bin. This is made
using PyInstaller.
Installation for Windows
Right click on ./atomizer/build_sbmlTranslator_win.ps1 and select Run with PowerShell.
Execution
./sbmlTranslator -i /path/to/sbml/file [-a] [-o output.bngl]

Optional arguments
  • [-a] activates the atomizer. Otherwise only a flat translation will be provided (no molecular structure)
  • [-p] activates pathway commons querying. An internet connection is required
  • [-b <path/to/bionetgen>] Enables post atomization analysis.
  • See [-h] for a full list of arguments
Directory Structure:
  • SBMLparser: Directory containing the main project.

    • sbmlTranslator.py: Entry level file
    • atomizer: Contains the main implicit assumption extraction code
      • analyzeSBML.py: lexical analysis engine
      • detectOntology.py: helper file for the lexical analysis engine
(levenshtein distance, convention discovery, etc.)
      • analyzeRDF.py: extracts annotation information and gets it into the
atomizer data model
      • resolveSCT.py: Creates the species composition table using lexical
analysis, annotation information and the stoichiometry matrix
      • moleculeCreation.py: Creates the structured molecules for use in
graph-creation
    • utils: contains several utility scripts used during the atomization process
      • consoleCommands.py: Interfaces with the BioNetGen console
      • pathwaysCommons.py: Queries BioGrid and pathways commons given an RDF annotation entry
  • stats: Extracts statistics of a set of atomized BioModels files
About
RNM to RBM translation project. 
ruleworld.github.io/atomizer/
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
19 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
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var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
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var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
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return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
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}
cleanLinks();
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mutations.forEach(function(m) {
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});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - RuleWorld/atomizer: RNM to RBM translation project. · GitHub
Skip to content
BranchesTags
Repository files navigation
Project for the translation of SBML files into BNGL files. You can find more
information about the project here.
Build StatusBuild status
Download Latest Test Builds
These builds are the from the head of master and are not guaranteed to be
stable. Use at your own risk.
Requirements
You should use Python 3.5 or later. A number of Python libraries need to be
installed, but these can be automatically installed in a Python virtual
environment, which is exactly what the makefile does under Linux and OSX or
what the PowerShell script does for Windows.
Ubuntu
sudo apt-get install -y python3-dev
sudo apt-get install -y python3-venv

Windows 10
You'll need to install Python 3. We recommend using Anaconda for this.
Optional for Developers
If you want to run ./atomizer/SBMLparser/sbmlTranslator.py directly, you can
install all the Python requirements at the system level by doing:
cd SBMLparser
sudo pip3 install -r requirements.txt

Alternatively, you can do this at the user level:
cd SBMLparser
pip3 install --user -r requirements.txt

Installation
OSX and Linux
From the top-level directory, type the following:
make; make install

This will create an sbmlTranslator binary in ./atomizer/bin. This is made
using PyInstaller.
Installation for Windows
Right click on ./atomizer/build_sbmlTranslator_win.ps1 and select Run with PowerShell.
Execution
./sbmlTranslator -i /path/to/sbml/file [-a] [-o output.bngl]

Optional arguments
  • [-a] activates the atomizer. Otherwise only a flat translation will be provided (no molecular structure)
  • [-p] activates pathway commons querying. An internet connection is required
  • [-b <path/to/bionetgen>] Enables post atomization analysis.
  • See [-h] for a full list of arguments
Directory Structure:
  • SBMLparser: Directory containing the main project.

    • sbmlTranslator.py: Entry level file
    • atomizer: Contains the main implicit assumption extraction code
      • analyzeSBML.py: lexical analysis engine
      • detectOntology.py: helper file for the lexical analysis engine
(levenshtein distance, convention discovery, etc.)
      • analyzeRDF.py: extracts annotation information and gets it into the
atomizer data model
      • resolveSCT.py: Creates the species composition table using lexical
analysis, annotation information and the stoichiometry matrix
      • moleculeCreation.py: Creates the structured molecules for use in
graph-creation
    • utils: contains several utility scripts used during the atomization process
      • consoleCommands.py: Interfaces with the BioNetGen console
      • pathwaysCommons.py: Queries BioGrid and pathways commons given an RDF annotation entry
  • stats: Extracts statistics of a set of atomized BioModels files
About
RNM to RBM translation project. 
ruleworld.github.io/atomizer/
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
19 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - RuleWorld/atomizer: RNM to RBM translation project. · GitHub
Skip to content
BranchesTags
Repository files navigation
Project for the translation of SBML files into BNGL files. You can find more
information about the project here.
Build StatusBuild status
Download Latest Test Builds
These builds are the from the head of master and are not guaranteed to be
stable. Use at your own risk.
Requirements
You should use Python 3.5 or later. A number of Python libraries need to be
installed, but these can be automatically installed in a Python virtual
environment, which is exactly what the makefile does under Linux and OSX or
what the PowerShell script does for Windows.
Ubuntu
sudo apt-get install -y python3-dev
sudo apt-get install -y python3-venv

Windows 10
You'll need to install Python 3. We recommend using Anaconda for this.
Optional for Developers
If you want to run ./atomizer/SBMLparser/sbmlTranslator.py directly, you can
install all the Python requirements at the system level by doing:
cd SBMLparser
sudo pip3 install -r requirements.txt

Alternatively, you can do this at the user level:
cd SBMLparser
pip3 install --user -r requirements.txt

Installation
OSX and Linux
From the top-level directory, type the following:
make; make install

This will create an sbmlTranslator binary in ./atomizer/bin. This is made
using PyInstaller.
Installation for Windows
Right click on ./atomizer/build_sbmlTranslator_win.ps1 and select Run with PowerShell.
Execution
./sbmlTranslator -i /path/to/sbml/file [-a] [-o output.bngl]

Optional arguments
  • [-a] activates the atomizer. Otherwise only a flat translation will be provided (no molecular structure)
  • [-p] activates pathway commons querying. An internet connection is required
  • [-b <path/to/bionetgen>] Enables post atomization analysis.
  • See [-h] for a full list of arguments
Directory Structure:
  • SBMLparser: Directory containing the main project.

    • sbmlTranslator.py: Entry level file
    • atomizer: Contains the main implicit assumption extraction code
      • analyzeSBML.py: lexical analysis engine
      • detectOntology.py: helper file for the lexical analysis engine
(levenshtein distance, convention discovery, etc.)
      • analyzeRDF.py: extracts annotation information and gets it into the
atomizer data model
      • resolveSCT.py: Creates the species composition table using lexical
analysis, annotation information and the stoichiometry matrix
      • moleculeCreation.py: Creates the structured molecules for use in
graph-creation
    • utils: contains several utility scripts used during the atomization process
      • consoleCommands.py: Interfaces with the BioNetGen console
      • pathwaysCommons.py: Queries BioGrid and pathways commons given an RDF annotation entry
  • stats: Extracts statistics of a set of atomized BioModels files
About
RNM to RBM translation project. 
ruleworld.github.io/atomizer/
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
19 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
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el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - RuleWorld/atomizer: RNM to RBM translation project. · GitHub
Skip to content
BranchesTags
Repository files navigation
Project for the translation of SBML files into BNGL files. You can find more
information about the project here.
Build StatusBuild status
Download Latest Test Builds
These builds are the from the head of master and are not guaranteed to be
stable. Use at your own risk.
Requirements
You should use Python 3.5 or later. A number of Python libraries need to be
installed, but these can be automatically installed in a Python virtual
environment, which is exactly what the makefile does under Linux and OSX or
what the PowerShell script does for Windows.
Ubuntu
sudo apt-get install -y python3-dev
sudo apt-get install -y python3-venv

Windows 10
You'll need to install Python 3. We recommend using Anaconda for this.
Optional for Developers
If you want to run ./atomizer/SBMLparser/sbmlTranslator.py directly, you can
install all the Python requirements at the system level by doing:
cd SBMLparser
sudo pip3 install -r requirements.txt

Alternatively, you can do this at the user level:
cd SBMLparser
pip3 install --user -r requirements.txt

Installation
OSX and Linux
From the top-level directory, type the following:
make; make install

This will create an sbmlTranslator binary in ./atomizer/bin. This is made
using PyInstaller.
Installation for Windows
Right click on ./atomizer/build_sbmlTranslator_win.ps1 and select Run with PowerShell.
Execution
./sbmlTranslator -i /path/to/sbml/file [-a] [-o output.bngl]

Optional arguments
  • [-a] activates the atomizer. Otherwise only a flat translation will be provided (no molecular structure)
  • [-p] activates pathway commons querying. An internet connection is required
  • [-b <path/to/bionetgen>] Enables post atomization analysis.
  • See [-h] for a full list of arguments
Directory Structure:
  • SBMLparser: Directory containing the main project.

    • sbmlTranslator.py: Entry level file
    • atomizer: Contains the main implicit assumption extraction code
      • analyzeSBML.py: lexical analysis engine
      • detectOntology.py: helper file for the lexical analysis engine
(levenshtein distance, convention discovery, etc.)
      • analyzeRDF.py: extracts annotation information and gets it into the
atomizer data model
      • resolveSCT.py: Creates the species composition table using lexical
analysis, annotation information and the stoichiometry matrix
      • moleculeCreation.py: Creates the structured molecules for use in
graph-creation
    • utils: contains several utility scripts used during the atomization process
      • consoleCommands.py: Interfaces with the BioNetGen console
      • pathwaysCommons.py: Queries BioGrid and pathways commons given an RDF annotation entry
  • stats: Extracts statistics of a set of atomized BioModels files
About
RNM to RBM translation project. 
ruleworld.github.io/atomizer/
Resources
Readme
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3 stars
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19 watching
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4 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
GitHub - RuleWorld/atomizer: RNM to RBM translation project. · GitHub
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Project for the translation of SBML files into BNGL files. You can find more
information about the project here.
Build StatusBuild status
Download Latest Test Builds
These builds are the from the head of master and are not guaranteed to be
stable. Use at your own risk.
Requirements
You should use Python 3.5 or later. A number of Python libraries need to be
installed, but these can be automatically installed in a Python virtual
environment, which is exactly what the makefile does under Linux and OSX or
what the PowerShell script does for Windows.
Ubuntu
sudo apt-get install -y python3-dev
sudo apt-get install -y python3-venv

Windows 10
You'll need to install Python 3. We recommend using Anaconda for this.
Optional for Developers
If you want to run ./atomizer/SBMLparser/sbmlTranslator.py directly, you can
install all the Python requirements at the system level by doing:
cd SBMLparser
sudo pip3 install -r requirements.txt

Alternatively, you can do this at the user level:
cd SBMLparser
pip3 install --user -r requirements.txt

Installation
OSX and Linux
From the top-level directory, type the following:
make; make install

This will create an sbmlTranslator binary in ./atomizer/bin. This is made
using PyInstaller.
Installation for Windows
Right click on ./atomizer/build_sbmlTranslator_win.ps1 and select Run with PowerShell.
Execution
./sbmlTranslator -i /path/to/sbml/file [-a] [-o output.bngl]

Optional arguments
  • [-a] activates the atomizer. Otherwise only a flat translation will be provided (no molecular structure)
  • [-p] activates pathway commons querying. An internet connection is required
  • [-b <path/to/bionetgen>] Enables post atomization analysis.
  • See [-h] for a full list of arguments
Directory Structure:
  • SBMLparser: Directory containing the main project.

    • sbmlTranslator.py: Entry level file
    • atomizer: Contains the main implicit assumption extraction code
      • analyzeSBML.py: lexical analysis engine
      • detectOntology.py: helper file for the lexical analysis engine
(levenshtein distance, convention discovery, etc.)
      • analyzeRDF.py: extracts annotation information and gets it into the
atomizer data model
      • resolveSCT.py: Creates the species composition table using lexical
analysis, annotation information and the stoichiometry matrix
      • moleculeCreation.py: Creates the structured molecules for use in
graph-creation
    • utils: contains several utility scripts used during the atomization process
      • consoleCommands.py: Interfaces with the BioNetGen console
      • pathwaysCommons.py: Queries BioGrid and pathways commons given an RDF annotation entry
  • stats: Extracts statistics of a set of atomized BioModels files
About
RNM to RBM translation project. 
ruleworld.github.io/atomizer/
Resources
Readme
Activity
Custom properties
Stars
3 stars
Watchers
19 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages