Network Analysis – Hands on

In this hands-on session you will go through some basic applications in network biology.
You will learn

  1. Where to find biological interaction data?
  2. How to use Cytoscape?
  3. How to visualize experimental data on a network?
  4. How to open a pathway as a network?
  5. How to extend a network with regulatory information?

The questions in part 2, 3 and 4 are meant to guide you through the practical session. You will receive all the answers at the end of the course. Feel free to ask the instructors if you need help with any steps in the practical.

Part 1: Learn how to use Cytoscape

We will go through this part together with you to show you how Cytoscape works.

Cytoscape ( is a popular and commonly used open source tool for network biology. The program has lots of different functionalities making it possible to perform a variety of network analysis, from the basics to advanced analysis. Since it is as open community project, many different researchers and developers contribute to Cytoscape. This is demonstrated by the wide variety of Cytoscape apps.
For the following two parts you will need different Cytoscape functionality that is explained in one of their tutorials online. You don’t need to go through the tutorials when you followed the introduction session.

Part 2: Using networks to analyze transcriptomics datasets

In this session we will continue using the dataset that you analyzed in the pathway analysis hands-on.
You can find the “dataset.xlsx” file in the network-analysis folder (in the zip file).

We will use the statistical results of the dataset from the paper “Gene Expression Patterns Induced by HPV-16 L1 Virus-Like Particles in Leukocytes from Vaccine Recipients” by Garcia-Pineres et al. published in The Journal of Immunology in 2008. We compare gene expression before and after vaccination.

Question 2A. Open the dataset.xlsx dataset in Excel. Create a table with the top 10 significantly up-regulated genes in the dataset.
Tip: in Excel go to Data → Sort → Sort by logFC from largest to smallest). Make sure the genes are significant (p-value < 0.05).

In the next step you will further investigate how the top 10 up-regulated genes are connected with each other. You will use GeneMania ( to find the interactions between the genes.

  • Copy the gene symbols of the genes (external_gene_id) in answer 2A and use them as the query on GeneMania.
  • Click on ‘Show advanced options’.
  • Make sure that only ‘Genetic interactions, Pathway and Physical Interactions’ are selected.
  • Make sure that you increase the number of related genes to 50.


Question 2B. Create the network with GeneMania. Make a screenshot. Are all nodes in the network connected?

Go to the “Functions” tab on the right side. GeneMania performs an over-repesentation analysis and provides a list of GO terms.

Question 2C. In what processes are the genes in the network involved? Are those processes expected to be changed after vaccination?

In the next step, we want to import this network in Cytoscape to visualize our experimental data on the gene nodes. Therefore, we need to download the network as text.

Then, we go to Cytoscape and import a network from the downloaded file (genemania_network.txt) – File → Import → Network → File.


Question 2D. When you opened the network in Cytoscape, make a screenshot. How many nodes and edges are in the network?
Tip: In the Network tab on the left, you can see the number of nodes and edges for all networks in a session.

Now, we want to import and visualize the gene expression dataset (network-analysis/dataset.xlsx) in the network. Follow the same instructions as in the introduction tutorial for importing data.
Make sure that you link the correct ID column to the correct key column:


Question 2E. Import the gene expression data (File → Import → Table → File → dataset.xlsx. Then create a visualization for the logFC for the node fill color using a gradient from blue (-1) to white (0) to red (+1).
Make a screenshot of the network. How many genes are up- and down-regulated? How many genes are not measured in the experiment?
Tip: You can also sort the table in Cytoscape by clicking on the column header.

Part 3: Biological pathways as networks

Open a new session in Cytoscape: File → New → Session.

In this part, we are going to open a pathway from WikiPathways as a network and extend it with regulatory interactions. We will use two different Cytoscape apps: WikiPathways and CyTargetLinker. The installation instructions (sent a week ago) explain how to install apps in Cytoscape.

First we are going to open the Type II Interferon Signaling Pathway in Cytoscape. You can find the GPML file in the network-analysis folder.

  1. File → Import → Network → File…
  2. Select network-analysis/WP619_71168.gpml
  3. Make sure you select “Network” in the first properties dialog:


Question 3A. Make a screenshot of the network. How many nodes and edges are present in the pathway?

Use the NetworkAnalyzer to calculate the different network properties that were discussed during the lecture. Go to Tools → NetworkAnalyzer → Analyze Network. Treat the network as undirected.

Question 3B. Look at the node degree distribution (in separate tab). What does the node degree distribution tell you about the nodes in the network?
Tip: Check lecture for explanation of node degree.

Question 3C. Look at the betweenness centrality distribution (in separate tab). Can you see a correlation between the number of neighbors and the betweenness?
In general: Is the betweenness always higher for nodes with a lot of neighbors? Why / why not?
Tip: Check lecture for explanation of node betweenness.

Next, we are going to use intuitive visualization of the node degree to easily find hub proteins in the network.

Question 3D. In the NetworkAnalyzer dialog, click on “Visualize Parameters”. Select the node degree as node color gradient (Map node color to → Select “Degree”).
Can you find hub proteins in the network?

Part 4: Regulatory interactions

In this part, we will use the pathway network from Part 3. Now, we will extend the network with regulatory information. We will investigate which microRNAs and drugs are regulating which proteins in the pathway. For this step, we will use the CyTargetLinker app for Cytoscape.
The regulatory information is provided as networks, called Regulatory Interaction Networks (RegINs). For this practical the miRTarBase and the DrugBank RegIN are stored in the downloaded zip file in the directory “network-analysis/RegINs“.

We are going to extend the Type II Interferon Signaling Pathway with regulatory information.

  • Click on Apps → CyTargetLinker → Extend Network
  • Select User Network → choose the network name of the pathway network
  • Select Network Attribute → choose the name of the column containing a biological identifier (“GeneID”)
  • Select Datasource Networks → Browse for the directory which contains the RegINs (network-analysis/RegINs)
  • Select Direction → “Add regulators”


Question 4A. How many drug-target and microRNA-target interactions were added to the network?
Tip: Check the CyTargetLinker tab on the left side.

Question 4B. Mention at least one gene that is regulated by both, drugs and microRNAs.

For the next questions, it is easier if you hide the microRNA-target interactions from miRTarBase. Go to the CyTargetLinker tab on the left and use the drop-down box next to the miRTarBase RegIN to hide the interactions.


Question 4C. Which genes are targeted by many different drugs?

Question 4D. Can you find drugs that target multiple genes? Provide the DrugBank ID (DB…) and the name of the drug(s).

For the next questions, it is easier if you hide the drug-target interactions from DrugBank. Go to the CyTargetLinker tab on the left and use the drop-down box next to the DrugBank RegIN to hide the interactions. Make sure that the miRTarBase interactions are shown!

Question 4E. Which gene is regulated by most microRNAs?

Question 4F. Can you find microRNAs that target multiple genes?