Help Page

Workspace Section

In this section, users are able upload four (4) input files to workspace.

1. GEO Series (GSE):
Lists of gene intensities that together form a single experiment. Details concering GSE data can be found on Gene Expression Omnibus, while GSE data can be found here.
Download a sample GSE file (GSE3744) that contains Gene expressions for a total of 47 human tissue breast tumor cases with conotrols.
Download a sample GSE file (GSE23066) that contains Gene expressions for 10 human tissue lung tumor cases with conotrols.
Download a sample GSE file (GSE31189) that contains Gene expressions for 92 human tissue bladder tumor cases with conotrols.
Download a sample GSE file (GSE28146) that contains Gene expressions for 30 human tissue Alzheimer´┐Żs Disease cases with conotrols.

2. GEO Annotation File (GPL):
This files accompanies each GSE file and contatin information regarding the microarray platform that has been used. Details concering GSE data can be found on Gene Expression Omnibus, while GPL data can be found here.
Download a sample GPL annotation file that contains information regarding Genes of found on GSE3744, GSE23066, GSE31189 and GSE28146.

3. Class labels:
A file that describes the class for each experiment. This information can be found on the GSE file.
Download a sample file that contains information regarding classes for GSE3744.
Download a sample file that contains information regarding classes for GSE23066.
Download a sample file that contains information regarding classes for GSE31189.
Download a sample file that contains information regarding classes for GSE28146.

4. Seed Genes:
A file that contain the Seed genes under investigation.
Download a sample file that contains 100 seed genes for GSE3744.
Download a sample file that contains 100 seed genes for GSE23066.
Download a sample file that contains 100 seed genes for GSE31189.
Download a sample file that contains 100 seed genes for GSE28146.



5. Upload Data to Workspace:
After selecting all the previously mentioned input files, data can be uploaded to Workspace by pressing the "Upload to Workspace" Button.
6. Upload Sample Data to Workspace:
By pressing the "Upload Sample to Workspace" Button, users may use a sample set (GSE3744).



Reconstruction of gene regulatory networks Section

In this section, users are able to generate reconstruction methods.

1. Select Methods:
Enable reconstruction methods by ckecking the corresponding checkbox.

2. Generate Reconstructed networks:
By pressing the "Generate Networks" button, selected reconstructed networks for each class are generated.

3. Download Reconstructed networks:
By pressing the appropriate button, selected reconstructed network can be donwloaded for further use.





Random Walks with Restarts Section

Random Walk with restarts is performed to each network.

1. Select Method:
Enable random walk with restarts method using the corresponding reconstructed network.

2. Generate random walk with restarts simulated network:
By pressing the "Generate" button, selected simulated networks for each class are generated.

3. Download simulated networks:
By pressing the appropriate button, selected simulated network can be donwloaded for further use. In addition, vizualisation of the generated simulated networks can be performed by pressing the "Vizualise--Networks" button



1. Select Vizualisation layout:
Enable random or circular network vizualisation layout.

2. Select a specific node with its first neighbours:
Select from the drop down menu the appropriate gene with its first neigbours.

3. View simulated networks:
By pressing the appropriate select box, exlusive class1, exlusive class2 and common on class1 and class2 edges are displayed

4. Further Visualization filters:
Move sliders accordingly so as to filter nodes and edges with value lower than the selected threshold

5. Navigation panel:
Apart from classical graph manipulation using mouse pad, navigation panel is also available to support smartphone/tablet users.



Workspace
Generated Reconstructed Networks
Random Walk Simulated Networks