Inferring Genetic Interaction Networks from Expression data

Data-File Format: Expression data / Column information data

Retrieve Inference-Results and Check Current Status

Three modes: Local PC Inference, Remote Server Inference, and Retrieve Results

There are three tabs on the main menu of MONET software; Use Local PC, Use Remote Server, Retrieve Analysis-Results. Users can perform network inference using our supercomputing center resources as well as user's local PC. If you have genome-scale data, it is better to utilize remote supercomputing resources. Rather, for small data you can use local PC resources. After job submission, you can retrieve current status or analysis results.

Tutorial

If you execute Cytoscape software, you can see the MONET menu on the 'Plugins' tab like the figure below.

Local PC Mode

Data-File Format: Expression data / Column information data

Remote Server Mode

Data-File Format: Expression data / Column information data

If you click the signup button, you can see the subscription page below and can create your account by filling out the simple form.

Retrieve Analysis-Results

As changing the confidence slider appeared in the figure above, users are able to have different interaction network results. Below are examples whose confidence level is 80 and 100 respectively.

If you select the previous job in analysis now, you can check current analysis status of the job or can cancel it. The current status also gives us remaining time of the job as shown in the figure below.

Usage of Customized Learning

If you click 'Customized Learning' button on the main panel, after couples of seconds you will see the panel of modularization status shown below.

MONET paper: Phil Hyoun Lee, Doheon Lee, Modularized learning of genetic interaction networks from biological annotations and mRNA expression data. Bioinformatics. 2005, 21:2739-2747

If you decrease the seed threshold by adjusting the slider, you will have more modules than before.

If you increase the mutual information (MI) and annotation information (AI) threshold, you will have smaller modules than before.