• Ewald J., Zhou, G., Lu, Y., Kolic, J., Ellis, C., Johnson, J.D., Macdonald P.E. and Xia, J. (2024) Web-based multi-omics integration using the Analyst software suite. Nature Protocols 19, 1467–1497
  • Zhou G., Pang Z., Lu Y., Ewald J., and Xia J. (2022) OmicsNet 2.0: a web-based platform for multi-omics integration and network visual analytics. Nucleic Acids Research, 50, W1.
  • Zhou, G., Li, S., Xia, J. (2020). Network-Based Approaches for Multi-omics Integration. Computational Methods and Data Analysis for Metabolomics, 2104, Humana, New York, NY.
  • Zhou, G. and Xia, J. (2019) Using OmicsNet for Network Integration and 3D Visualization. Current Protocols in Bioinformatics, 65, e69.
  • Zhou G. and Xia J. (2018) OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space. Nucleic Acids Research, 46, W1.


The web interfaces of OmicsNet are designed to be self-explanatory. In cases of limited space, mouse-over balloon helps are available. The following tutorials are meant to complement the aforementioned information by providing step-by-step instructions for several of the most common tasks. Please note, due to frequent updates, some screenshot illustrations may be outdated. Therefore, we ask that users do not take those steps verbatim. Instead, users should focus on the the concepts and the workflow for data analysis and interpretation.

Source Code

OmicsNet is implemented based on the JavaServer Faces framework using the PrimeFaces library ( The backend computing is based on R using the OmicsNetR package. The interactive visualization is based on the JavaScripts and leverages the WebGL technology for 3D visualization. We encourage users to use the public web servers for flexible and interactive data analysis tasks, and the R packages for batch processing. The source code is provided mainly for transparency. It is not intended to run as production server which requires advanced system admin expertise to set up and to maintain.