Studying gene functions through the networks

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Gene2Net CPTAC portal contains the highly functinally relevant breast, colorectal, and ovarian cancer protein co-expression networks that can be used to study gene functions.


The detailed information about three protein co-expression networks can be found below.

Data sets Number of nodes Number of edges
Breast Cancer 5756 19907
Colorectal Cancer 3660 13101
Ovarian Cancer 2431 5681

Please follow the workflow below to analyze your favorite gene or gene list:

1. Select the cancer type and network construction method.
2. Set the number of output genes if selecting "Network Expansion" as the network construction method.
3. Input your favorite gene or list using gene symbols. If the input genes are in the network, genes will be shown in the "Gene symbols in the network" text area. Otherwise, they will be shown in the "Gene symbols not in the network" text area.
4. Retrieve the top n (set in Step 2) genes with the highest random walk scores if selecting "Network Expansion" method.
5. Visualize the co-expression network among input seeds and retrieved genes if selecting "Network Expansion" method. Visualize the network between input seeds if selecting "Network Retrieval" method. The system also performs GO enrichment analysis based on the nodes in the network and visualize the results as a DAG structure.


Gene2Net CPTAC portal is now available to study gene functions in the context of protein co-expression networks.

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Gene2Net is developed and maintained by Jing Wang, David Ma and Bing Zhang at the Zhang Lab. Funding credit: NIH/NCI (U24 CA159988); NCI/Leidos (13XS029, 15X038).