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| #acl BaderLabGroup:read,write,revert,delete All: We can migrate some of the content from the MCODE site here: http://cbio.mskcc.org/~bader/software/mcode/ |
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| MCODE is a Cytoscape !PlugIn that finds clusters (highly interconnected regions) in any network loaded into Cytoscape. Depending on the type of network, clusters may mean different things. For instance, clusters in a protein-protein interaction network have been shown to be protein complexes and parts of pathways. Clusters in a protein similarity network represent protein families. | MCODE is a [http://cytoscape.org Cytoscape] plugin that finds clusters (highly interconnected regions) in a network. Clusters mean different things in different types of networks. For instance, clusters in a protein-protein interaction network are often protein complexes and parts of pathways, while clusters in a protein similarity network represent protein families. [http://cytoscape.org Cytoscape] is freely available network visualization and analysis software. |
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| MCODE is a relatively fast method of clustering, although it does not currently provide any statistical score on the resulting clusters. It can be used as discovery tool when analyzing a network. See the paper for more information. | * Coming Soon: Run MCODE v1.2.1 using Java !WebStart MCODE is a relatively fast method of clustering. With an intuitive interface, it is suited for both computationally and biologically oriented researchers. Current features include: * Fast network clustering * Fine-tuning of results with numerous node-scoring and cluster-finding parameters * Interactive cluster boundary and content exploration * Multiple result set management * Cluster sub-network creation and plain text export Currently, MCODE does not provide any statistical score on the resulting clusters but can be used as a discovery tool in network analysis. Please see the [http://www.biomedcentral.com/1471-2105/4/2 MCODE paper] for more information. Also be sure to consult the [:Software/MCODE/UsersManual: documentation] for screen shots, descriptions, and tutorials. |
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| == Downloads == | == Latest Download == With Cytoscape 2.5.1, you can download the latest MCODE version directly from within the software using the Plugin Manager (Plugins > Manage Plugins). MCODE is found under the Analysis category. The current MCODE Cytoscape plugin is MCODE v1.2.1: [attachment:MCODE_v1_2_1.zip Download the latest version] * Plugin requires [http://www.cytoscape.org/ Cytoscape v2.5.1 or later] and [http://java.sun.com/j2se/1.5.0/index.jsp Java 1.5.0] * See the [:Software/MCODE/UsersManual: documentation] == Previous Versions == |
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| * plugin * requires Cytoscape v2.3.2 or later * Javadoc |
* [attachment:MCODE_v1_2.zip Download MCODE v1.2] * requires Cytoscape v2.3 to v2.4 |
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| * plugin | * [attachment:MCODE_v1_1.zip Download MCODE v1.1] |
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| * Javadoc * Run using Java WebStart |
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| * plugin | * [attachment:MCODE_v1_0.zip Download MCODE v1.0] |
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=== Cytoscape === * Link to cytoscape page |
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| == User's Manual == === Installation === === Introduction === === Advanced Techniques === === Tutorials === === Index === |
== Literature and Resources == === MCODE Publication === Please see the following paper for more information about the algorithm: * Bader GD, Hogue CW. . An automated method for finding molecular complexes in large protein interaction networks. . ''BMC Bioinformatics''. 2003 Jan 13;4(1):2. . http://www.biomedcentral.com/1471-2105/4/2 === Documentation === The [:Software/MCODE/UsersManual: MCODE User's Manual] is both a great place to start learning the basics and a helpful reference for expert users. It includes installation instructions, explanations, definitions, examples and tutorials to help you produce, interpret, output, and validate results. === Cytoscape Tutorials === A great deal of introductory and advanced tutorials are available at the [http://www.cytoscape.org/tut/tutorial.php Cytoscape Tutorial Resource]. '''Section 7: Modules and Complexes''' incorporates MCODE, and several other plugins, in a complex discovery and validation excercise. |
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| * Ability to run MCODE from the command line * Automation of * Robustness tests * Gene function over-representation analysis * Benchmarking: result comparison and validation using cluster benchmark * Attribute-enhanced clustering: consideration of user attributes, like expression data, in the clustering algorithm |
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| If you encounter a bug with this !PlugIn, or have a feature suggestion, please e-mail GaryBader. Be sure to take a look at the Future Developments section before e-mailing a feature request. | If you encounter a bug with this plugin, or have a feature suggestion, please e-mail [:GaryBader: Gary Bader]. Be sure to take a look at the Future Developments section before e-mailing a feature request. |
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| This software is open-source. If you modify the source code and would like the modification to be included in a subsequent release, I would love to hear from you. Please send me an e-mail to GaryBader. | This software is open-source. If you modify the source code and would like the modification to be included in a subsequent release, we would love to hear from you. Please send me an e-mail to [:GaryBader: Gary Bader]. === Software Development === If you are a software developer, the MCODE algorithm is easy to incorporate into your own Java software. Just download the source code to get started. * MCODE source code and Javadoc are made available through Subversion (SVN), a version control repository. * SVN Account Access: [http://chianti.ucsd.edu/svn/csplugins/trunk/mskcc/gbader/MCODEv1.2/ MCODE directory] * Quick-Link: [http://chianti.ucsd.edu/svn/csplugins/trunk/mskcc/gbader/MCODEv1.2/javadoc/index.html Javadoc] * The Cytoscape developer wiki provides some detailed instructions on using SVN: http://cytoscape.org/cgi-bin/moin.cgi/SVN_Access |
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| == Acknowledgements == | == Credits == |
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| This software was originally released as a command-line-only program from the Hogue Lab. It was created by Gary Bader, currently based in the [http://www.baderlab.org/home/ Bader Lab] at the University of Toronto (formerly in the Sander Group,[http://www.cbio.mskcc.org/ Computational Biology Center, Memorial Sloan-Kettering Cancer Center], New York City) | Version 1.2 was produced by [:VukPavlovic: Vuk Pavlovic] in the Bader Lab. Special thanks to Christopher Workman (The Technical University of Denmark) and Carlo Laudanna (University of Verona) for their expert input during beta-testing. |
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| Version 1.2 was produced by Vuk Pavlovic in the Bader Lab. | This software was originally released as a command-line-only program from the Hogue Lab. It was created by [:GaryBader: Gary Bader], currently based in the [:Home:Bader Lab] at the University of Toronto (formerly in the Sander Group, [http://www.cbio.mskcc.org/ Computational Biology Center, Memorial Sloan-Kettering Cancer Center], New York City) |
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Please see the following paper for more information about the algorithm: * Bader GD, Hogue CW. . An automated method for finding molecular complexes in large protein interaction networks. . ''BMC Bioinformatics''. 2003 Jan 13;4(1):2. . http://www.biomedcentral.com/1471-2105/4/2 |
attachment:MCODELogo.png
MCODE is a [http://cytoscape.org Cytoscape] plugin that finds clusters (highly interconnected regions) in a network. Clusters mean different things in different types of networks. For instance, clusters in a protein-protein interaction network are often protein complexes and parts of pathways, while clusters in a protein similarity network represent protein families. [http://cytoscape.org Cytoscape] is freely available network visualization and analysis software.
Coming Soon: Run MCODE v1.2.1 using Java WebStart
MCODE is a relatively fast method of clustering. With an intuitive interface, it is suited for both computationally and biologically oriented researchers. Current features include:
- Fast network clustering
- Fine-tuning of results with numerous node-scoring and cluster-finding parameters
- Interactive cluster boundary and content exploration
- Multiple result set management
- Cluster sub-network creation and plain text export
Currently, MCODE does not provide any statistical score on the resulting clusters but can be used as a discovery tool in network analysis. Please see the [http://www.biomedcentral.com/1471-2105/4/2 MCODE paper] for more information. Also be sure to consult the [:Software/MCODE/UsersManual: documentation] for screen shots, descriptions, and tutorials.
Latest Download
With Cytoscape 2.5.1, you can download the latest MCODE version directly from within the software using the Plugin Manager (Plugins > Manage Plugins). MCODE is found under the Analysis category. The current MCODE Cytoscape plugin is MCODE v1.2.1: [attachment:MCODE_v1_2_1.zip Download the latest version]
Plugin requires [http://www.cytoscape.org/ Cytoscape v2.5.1 or later] and [http://java.sun.com/j2se/1.5.0/index.jsp Java 1.5.0]
- See the [:Software/MCODE/UsersManual: documentation]
Previous Versions
MCODE v1.2
- [attachment:MCODE_v1_2.zip Download MCODE v1.2]
- requires Cytoscape v2.3 to v2.4
MCODE v1.1
- [attachment:MCODE_v1_1.zip Download MCODE v1.1]
- requires Cytoscape v2.1
MCODE v1.0
- [attachment:MCODE_v1_0.zip Download MCODE v1.0]
- requires Cytoscape v2.0
Literature and Resources
MCODE Publication
Please see the following paper for more information about the algorithm:
- Bader GD, Hogue CW.
- An automated method for finding molecular complexes in large protein interaction networks.
BMC Bioinformatics. 2003 Jan 13;4(1):2.
Documentation
The [:Software/MCODE/UsersManual: MCODE User's Manual] is both a great place to start learning the basics and a helpful reference for expert users. It includes installation instructions, explanations, definitions, examples and tutorials to help you produce, interpret, output, and validate results.
Cytoscape Tutorials
A great deal of introductory and advanced tutorials are available at the [http://www.cytoscape.org/tut/tutorial.php Cytoscape Tutorial Resource]. Section 7: Modules and Complexes incorporates MCODE, and several other plugins, in a complex discovery and validation excercise.
Future Developments
- Ability to run MCODE from the command line
- Automation of
- Robustness tests
- Gene function over-representation analysis
- Benchmarking: result comparison and validation using cluster benchmark
- Attribute-enhanced clustering: consideration of user attributes, like expression data, in the clustering algorithm
Contact
Bugs / Feature Requests
If you encounter a bug with this plugin, or have a feature suggestion, please e-mail [:GaryBader: Gary Bader]. Be sure to take a look at the Future Developments section before e-mailing a feature request.
Collaboration
This software is open-source. If you modify the source code and would like the modification to be included in a subsequent release, we would love to hear from you. Please send me an e-mail to [:GaryBader: Gary Bader].
Software Development
If you are a software developer, the MCODE algorithm is easy to incorporate into your own Java software. Just download the source code to get started.
- MCODE source code and Javadoc are made available through Subversion (SVN), a version control repository.
SVN Account Access: [http://chianti.ucsd.edu/svn/csplugins/trunk/mskcc/gbader/MCODEv1.2/ MCODE directory]
Quick-Link: [http://chianti.ucsd.edu/svn/csplugins/trunk/mskcc/gbader/MCODEv1.2/javadoc/index.html Javadoc]
The Cytoscape developer wiki provides some detailed instructions on using SVN: http://cytoscape.org/cgi-bin/moin.cgi/SVN_Access
Credits
Version 1.2 was produced by [:VukPavlovic: Vuk Pavlovic] in the Bader Lab. Special thanks to Christopher Workman (The Technical University of Denmark) and Carlo Laudanna (University of Verona) for their expert input during beta-testing.
This software was originally released as a command-line-only program from the Hogue Lab. It was created by [:GaryBader: Gary Bader], currently based in the [:Home:Bader Lab] at the University of Toronto (formerly in the Sander Group, [http://www.cbio.mskcc.org/ Computational Biology Center, Memorial Sloan-Kettering Cancer Center], New York City)
This software is made available under the [http://www.gnu.org/copyleft/lesser.html LGPL] (Lesser General Public License), which means that you can freely use it within your own software, but if you alter the code itself and distribute it, you must make the source code alterations freely available as well.