Standalone Version      
 
  Standalone Version  
Menu - File:
 
As input GeneNetFinder takes either gene expression data or regulation rules.
Load gene expression data: load the raw value of gene expression data in text file.
Load regulation rules: load regulation rules of gene regulatory networks in .rule format.
Exit: Quit the program.
Menu - Operations:
 
After loading the gene expression data, click "Visualize identified gene regulations" to visualize a gene regulatory network. GeneNet Finder provides two layout methods:
Grid Layout: gene regulatory network as an orthogonal drawing with nodes in grid points.
Layered layout: gene regulatory network as a layered graph.
Circular layout: visualizing gene regulatory networks in circle.
Click "Save image as" to save your visualization.
 
Menu - Data:
 
Click "Analyze input data" to analyze the gene expression data.
The menu "Identified gene regulations" shows the identified gene regulations from the input data.
Save identified regulations as: save your result.
Menu - Options:
 
View regulations identified: show or hide the regulations identified panel.
View Node list: show or hide the node list listbox.
Setting: more settings of GeneNet Finder.
Menu - Setting:
 
Some settings of GeneNet Finder
Show identified regulations: set/unset the default setting of the regulations identified panel.
Show node list: set/unset the default setting of the node list listbox.
Show edge labels: set/unset the default setting of edge labels.
Interface:
  

 

Analysis of gene expression data
 

 

Setting time points
 

 

Identified gene regulations
 

 

Identified gene regulations with multiple regulators
  Gene regulations in the dataset of genes in the yeast cell cycle
 
  Gene regulations in the dataset of genes in the human cell cycle
 
Recommended operational process:
  File -> Load gene expression data -> Operations -> Visualize identified regulations -> Save (image/regulations)
  File -> Load regulation rules -> Layout -> Grid layout/ Circular layout -> File -> Save as image
   

 

 

 
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Biocomputing Lab, Department of Computer Science and Engineering, Inha University.
Incheon, 402-751, South Korea. Phone: +82-32-8607388, Fax: +82-32-8634386