BisoGenet: a new tool for gene network building, visualization and analysis

By Alexander Martin, M. Ochagavía, Laya C. Rabasa, Jamilet Miranda, J. Fernández-de-Cossio, R. Bringas. BMC Bioinformatics, 2010

315 citations recorded by the source corpus.

BackgroundThe increasing availability and diversity of omics data in the post-genomic era offers new perspectives in most areas of biomedical research. Graph-based biological networks models capture the topology of the functional relationships between molecular entities such as gene, protein and small compounds and provide a suitable framework for integrating and analyzing omics-data. The development of software tools capable of integrating data from different sources and to provide flexible methods to reconstruct, represent and analyze topological networks is an active field of research in bioinformatics.ResultsBisoGenet is a multi-tier application for visualization and analysis of biomolecular relationships. The system consists of three tiers. In the data tier, an in-house database stores genomics information, protein-protein interactions, protein-DNA interactions, gene ontology and metabolic pathways. In the middle tier, a global network is created at server startup, representing the whole data on bioentities and their relationships retrieved from the database. The client tier is a Cytoscape plugin, which manages user input, communication with the Web Service, visualization and analysis of the resulting network.ConclusionBisoGenet is able to build and visualize biological networks in a fast and user-friendly manner. A feature of Bisogenet is the possibility to include coding relations to distinguish between genes and their products. This feature could be instrumental to achieve a finer grain representation of the bioentities and their relationships. The client application includes network analysis tools and interactive network expansion capabilities. In addition, an option is provided to allow other networks to be converted to BisoGenet. This feature facilitates the integration of our software with other tools available in the Cytoscape platform. BisoGenet is available at http://bio.cigb.edu.cu/bisogenet-cytoscape/.

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ecbfbad53fb69e1185134a1b1c935674df7420cd

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In Artificial Intelligence

  1. Ruth Nussinov
  2. Peter Csermely
  3. Huba J. M. Kiss
  4. Tamás Korcsmáros
  5. Gabor London

In Molecular Biology

  1. Ruth Nussinov
  2. Peter Csermely
  3. Huba J. M. Kiss
  4. Tamás Korcsmáros
  5. Gabor London
  6. Alexandre M. J. J. Bonvin
  7. D. Ritchie
  8. David Baker

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