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Open Access Highly Accessed Methodology article

BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies

Sergey Kozhenkov1, Mayya Sedova1, Yulia Dubinina1, Amarnath Gupta1, Animesh Ray3, Julia Ponomarenko12 and Michael Baitaluk1*

Author Affiliations

1 San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA

2 Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA

3 Keck Graduate Institute, 535 Watson Drive, Claremont, CA, 91711, USA

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BMC Systems Biology 2011, 5:7  doi:10.1186/1752-0509-5-7

Published: 14 January 2011

Abstract

Background

Understanding of immune response mechanisms of pathogen-infected host requires multi-scale analysis of genome-wide data. Data integration methods have proved useful to the study of biological processes in model organisms, but their systematic application to the study of host immune system response to a pathogen and human disease is still in the initial stage.

Results

To study host-pathogen interaction on the systems biology level, an extension to the previously described BiologicalNetworks system is proposed. The developed methods and data integration and querying tools allow simplifying and streamlining the process of integration of diverse experimental data types, including molecular interactions and phylogenetic classifications, genomic sequences and protein structure information, gene expression and virulence data for pathogen-related studies. The data can be integrated from the databases and user's files for both public and private use.

Conclusions

The developed system can be used for the systems-level analysis of host-pathogen interactions, including host molecular pathways that are induced/repressed during the infections, co-expressed genes, and conserved transcription factor binding sites. Previously unknown to be associated with the influenza infection genes were identified and suggested for further investigation as potential drug targets. Developed methods and data are available through the Java application (from BiologicalNetworks program at http://www.biologicalnetworks.org webcite) and web interface (at http://flu.sdsc.edu webcite).