title: Mango: combining and analyzing heterogeneous biological networks.
abstract: BACKGROUND
  Heterogeneous biological data such as sequence matches, gene expression correlations, protein-protein interactions, and biochemical pathways can be merged and analyzed via graphs, or networks. Existing software for network analysis has limited scalability to large data sets or is only accessible to software developers as libraries. In addition, the polymorphic nature of the data sets requires a more standardized method for integration and exploration.
  
  
  RESULTS
  Mango facilitates large network analyses with its Graph Exploration Language, automatic graph attribute handling, and real-time 3-dimensional visualization. On a personal computer Mango can load, merge, and analyze networks with millions of links and can connect to online databases to fetch and merge biological pathways.
  
  
  CONCLUSIONS
  Mango is written in C++ and runs on Mac OS, Windows, and Linux. The stand-alone distributions, including the Graph Exploration Language integrated development environment, are freely available for download from http://www.complex.iastate.edu/download/Mango. The Mango User Guide listing all features can be found at http://www.gitbook.com/book/j23414/mango-user-guide.
authors.affiliation: Department of Genetics, Development and Cell Biology, Iowa State University, Iowa, 50011 Ames USA.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Chang
authors.affiliation: Department of Genetics, Development and Cell Biology, Iowa State University, Iowa, 50011 Ames USA.
authors.forename: Hyejin
authors.initials: H
authors.lastname: Cho
authors.affiliation: Department of Genetics, Development and Cell Biology, Iowa State University, Iowa, 50011 Ames USA.|Department of Computer Science, Iowa State University, Iowa, 50011 Ames USA.
authors.forename: Hui-Hsien
authors.identifier: 0000-0002-2029-8743
authors.initials: HH
authors.lastname: Chou
keywords: 3D visualization; Biological pathway analysis; Graph mathematics; Heterogeneous data integration; Systems biology