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BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies
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 syste...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3027118/ https://www.ncbi.nlm.nih.gov/pubmed/21235794 http://dx.doi.org/10.1186/1752-0509-5-7 |
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author | Kozhenkov, Sergey Sedova, Mayya Dubinina, Yulia Gupta, Amarnath Ray, Animesh Ponomarenko, Julia Baitaluk, Michael |
author_facet | Kozhenkov, Sergey Sedova, Mayya Dubinina, Yulia Gupta, Amarnath Ray, Animesh Ponomarenko, Julia Baitaluk, Michael |
author_sort | Kozhenkov, Sergey |
collection | PubMed |
description | 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) and web interface (at http://flu.sdsc.edu). |
format | Text |
id | pubmed-3027118 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-30271182011-01-27 BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies Kozhenkov, Sergey Sedova, Mayya Dubinina, Yulia Gupta, Amarnath Ray, Animesh Ponomarenko, Julia Baitaluk, Michael BMC Syst Biol Methodology Article 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) and web interface (at http://flu.sdsc.edu). BioMed Central 2011-01-14 /pmc/articles/PMC3027118/ /pubmed/21235794 http://dx.doi.org/10.1186/1752-0509-5-7 Text en Copyright ©2011 Kozhenkov et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Article Kozhenkov, Sergey Sedova, Mayya Dubinina, Yulia Gupta, Amarnath Ray, Animesh Ponomarenko, Julia Baitaluk, Michael BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies |
title | BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies |
title_full | BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies |
title_fullStr | BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies |
title_full_unstemmed | BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies |
title_short | BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies |
title_sort | biologicalnetworks - tools enabling the integration of multi-scale data for the host-pathogen studies |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3027118/ https://www.ncbi.nlm.nih.gov/pubmed/21235794 http://dx.doi.org/10.1186/1752-0509-5-7 |
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