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Supporting Information for "Estimation of Protein and Domain Interactions in the Switching Motiliy System of Myxococcus Xanthus" PDF

In this section we list all the supporting information for the article Estimation of Protein and Domain Interactions in the Switching Motiliy System of Myxococcus xanthus . Input and output data are presented as well as the software to reproduce the results.

Last Updated ( Tuesday, 10 June 2008 14:08 )
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About Cytoprophet PDF

Cytoiprophet Logo

Cytoprophet is a project developed by the Laboratory for Computational Life Sciences at the Computer Science Department of the University of Notre Dame. It is a tool to help researchers to infer new potential protein (PPI) and domain (DDI) interactions. It is implemented as a Cytoscape plugin, where users input a set of proteins and retrieve a network of plausible protein and domain interactions with a score. Three algorithms are used for the estimation of PPI/DDI: Maximum Specificity Set Cover (MSSC) Approach, Maximum Likelihood Estimation (MLE) and the Sum-Product Algorithm (SPA) for protein networks. To see more details refer to Documentation.

Last Updated ( Wednesday, 02 April 2008 00:16 )
 
Supplementary Material for "Predicting Protein-Protein Interactions from Protein Domains Using a Set Cover Approach" PDF

 

Supplementary Material for Predicting Protein-Protein Interactions from Protein Domains Using a Set Cover Approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol 4 pp. 78-87. Jan-March 2007 can be found here. The portal for PPI predictions has been replaced by a Cytoscape plugin that can do protein and domain interaction predictions using the Maximum Specificity Set Cover Approach (MSSC) as well as other algorithms like Maximum Likelihood Estimation (MLE) and the Sum-Product Algorithm (SPA) for PPI/DDI prediction.

Last Updated ( Wednesday, 23 April 2008 22:53 )
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Cytoprophet Project Description PDF
Description of the project
Biological networks are an exciting topic in the field of computational biology and bioinformatics. They allow us to understand biological processes just as if they were nodes in a computer network. The fact that we can study them in that
fashion opens up a huge opportunity area for engineers and computer scientists to dive into science and do real discoveries, and help fight against diseases like Cancer and AIDS.
Protein Interaction Network
Example of a biological network in the organism C. elegans , better known as worm.
To be more specific, we are interested in how proteins interact inside the cell. Proteins are the workhorses of the cell, they perform most of the biological functions in our body. For example, Hemoglobin is an oxygen-transport protein that help us to stay alive. If we understand, how all these proteins interact, then we can have a much better understanding of what is life and use this knowledge to find ways to treat genetic diseases.
How is research done in this area? The way it works is the following: experimentalists siting in a wet lab do experiments to test if two proteins interact, they store the output of their experiments in databases that are available online. The more experiments they do, the more we know about the interactions and the better the picture of the network of proteins. However, once this information is online, there is a data processing stage that allow us to build hypotheses and reach conclusions about the inner workings of the proteins in the cell. This data processing stage is usually done by both biologists and computer scientists. The more tools we have the more opportunities we have to reach discoveries.
Cytoscape GUIAn important tool to study protein interaction networks is called Cytoscape (www.cytoscape.org). It is an open-source project that allows scientists and engineers to study biological networks in a systematic way.An interesting thing about Cytoscape is that it is extensible, this means that people from the community can contribute to it by developing plugins that introduce more analysis methods to improve research in this area.
Our group (LCLS) is working on algorithmic tools that learn from experimental data and other sources of information, like structural information of proteins, to predict novel protein interactions and even interactions of pieces of proteins called domains. In order to have a greater impact on the scientific community, we want to port our set of mathematical and algorithmic tools to a Cytoscape plugin. Doing this will allow more researchers to have access to our tools and use them to solve real life problems. Cytoscape is built in Java as well as its plugins.
Last Updated ( Thursday, 27 March 2008 22:35 )
 
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