Mango is a graph analysis and visualization software designed to handle many large graphs with tens of thousands of nodes and millions of links at once. Mango got its name from its purpose of Manipulation and Analysis of Networks and Gene Ontology. Mango combines the power and flexibility of a high level Graph Exploration Language (Gel) with the easy operation of a 3D graphical user interface. The result is a general purpose graph analysis tool that can be used to analyze many heterogeneous biological data sets. Mango is not limited to handling only biological data — Any data association and linkage information can be loaded into Mango and analyzed. If you've struggled to analyze or even load BIG DATA with other graph analysis tools, give Mango a try.
The collection of publicly available biological databases and meta databases that associate one type of data to the other is growing rapidly. The 2014 Nucleic Acids Research Database Special Issue documented 1552 online biological databases, and that number has grown to 1596 by the end of 2014. There is a need to effectively integrate and speed up the analysis of BIG DATA. Graphs represent the relationships among biological entities, and are a natural way to represent heterogeneous biological data in a cohesive manner. However, combining large biological data graphs is difficult due to their sizes and their different node and link attributes. Mango is developed to handle large graph data analysis and can easily combine different biological data graphs to enable the testing of novel biological hypotheses or to facilitate the integrated analysis of many different types of biological data networks. Developed as a general purpose graph analysis and visualization tool, Mango can have other potential applications unforeseen by its developers. We welcome interested users to download Mango and give it a try to see how Mango might help with your research.
How to download Mango
Since July 2016, Iowa State University Research Foundation has licensed the Mango software to Complex Computation LLC as its exclusive developer and distributor, thus Mango versions 1.24 or later should be obtained from Complex Computation LLC Mango download website.
If you wish to retreive Mango versions 1.23 or earlier which we archived here, follow the procedures below to download the older versions. However, we strongly recommend that you start using the latest versions of Mango as older versions are no longer being supported either by us or by Complex Computation LLC:
- Input your email address into the box at the following Registration section.
- Press "Enter" on your keyboard. You should be taken to a confirmation screen.
- Check your email; you should be getting an email from our automatic system with an assigned password shortly. If not, check your email spam filer and try again.
- After you have obtained the password, go to the Download page and input your email and password to login.
- Once you login, you should be taken to the Mango download page where you can download Mango for Mac, Windows or Linux.
Please register your email address below to obtain your download password. The registration is necessary for several reasons:
- We can send you email notices when newer versions of Mango become available;
- We can provide our grant agency anonymous usage statistics of our software; this helps keep us in business so we can continue to improve Mango to serve your needs better; and
- We filter all incoming emails against our registration list to remove spams. If you would like to send us a question or suggestion via emails, you need to register your email address firs. Otherwise, we will not receive your email inquiries.
Your email address will only be used for the purposes mentioned above. If you have forgotten your download password, you can also retrieve it by entering your email address again. Please input your email address below and then press the Return key to register:
Tutorials are being developed to help users better understand Mango. Tutorials introduce the most important features of Mango and gradually lead users to explore its full functionality and user interface. Users can quickly gain first-hand experience using Mango and begin graph analysis after completing the tutorials. Comprehensive Mango documentation in PDF formats are also being made available to be used as references. Look at the Mango Documentation page to see which tutorials and documents for Mango are available now.
You may send email to if you wish to report Mango bugs, make future feature requests or share your success stories using Mango. Please note that you must register first for your email to come through our spam filter system.
Mango development is partially supported by the National Science Foundation grant DBI-0850195, the Iowa State University Plant Sciences Institute Faculty Scholar Grant, and James Cornette Research Fellowship.
- Mango: combining and analyzing heterogeneous biological networks. Jennifer Chang; Hyejin Cho and Hui-Hsien Chou. BioData Mining. Accepted 2016.