BiNA: a visual analytics tool for biological network data

PLoS One. 2014 Feb 13;9(2):e87397. doi: 10.1371/journal.pone.0087397. eCollection 2014.

Abstract

Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA--the Biological Network Analyzer--a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computer Graphics
  • Data Mining / methods*
  • Database Management Systems*
  • Databases, Factual
  • Gene Regulatory Networks*
  • Humans
  • Metabolic Networks and Pathways*
  • Protein Interaction Mapping

Grants and funding

The work is supported in parts by: Deutsche Forschungsgemeinschaft (BIZ4:1-4) http://www.dfg.de/, Deutsche Forschungsgemeinschaft (SPP 1335 ‘Scalable Visual Analytics’) http://www.dfg.de/, Landesforschungsschwerpunktprogramm des Landes Baden-Württemberg, Klaus Tschira Foundation, German Cancer Aid (grant 107342), BMBF (grant number 01GI1104A), EU FP7 grants MARINA (contract no. 236215), PRIME-XS (contract no. 262067). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.