Mango: An Environment for Combining Massive Heterogeneous Networks

Biological data include diverse types such as sequences, gene expressions, protein-protein interactions, genome-wise associations, biochemical and genetic pathways, etc. Heterogeneous data can be merged within graphs, or networks, associating data to one another. However, analyzing modern heterogeneous biological data can easily overwhelm existing software. The complexity and polymorphic nature of modern biological data sets requires a more standardized method for integration, exploration and inference.

The Mango network analysis and visualization software enables the integration and analysis of large heterogeneous networks. Mango is highly scalable; it can load and merge several large networks containing up to 4 million links on a desktop computer. Mango facilitates network analyses with its integrated Graph Exploration Language and real-time visualization of intermediate analysis results. The Graph Exploration Language automates graph attribute merging and promotion among many graph types and contains rich expressive syntax for graph analyses. Mango provides 3D visualization of multiple graphs, allowing users to map data attributes to visual effects. Many sophisticated graph analysis functions such as force-directed layouts, traversal and subsetting of graphs, direct online network database queries, and import and export options, are built into Mango. To sum up, Mango provides a standard, fast, flexible and powerful method for integrating and analyzing massive heterogeneous biological networks, which can significantly speed up serendipitous discoveries in complex data.

Mango is a C++ program that runs on 32 and 64 bit versions of Mac, Windows and Linux. Mango provides a standalone environment for graph analysis and is freely available from http://www.complex.iastate.edu/download/Mango.