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Biana: a software framework for compiling biological interactions and analyzing networks

BACKGROUND: The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein...

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Autores principales: Garcia-Garcia, Javier, Guney, Emre, Aragues, Ramon, Planas-Iglesias, Joan, Oliva, Baldo
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3098100/
https://www.ncbi.nlm.nih.gov/pubmed/20105306
http://dx.doi.org/10.1186/1471-2105-11-56
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author Garcia-Garcia, Javier
Guney, Emre
Aragues, Ramon
Planas-Iglesias, Joan
Oliva, Baldo
author_facet Garcia-Garcia, Javier
Guney, Emre
Aragues, Ramon
Planas-Iglesias, Joan
Oliva, Baldo
author_sort Garcia-Garcia, Javier
collection PubMed
description BACKGROUND: The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. RESULTS: We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. CONCLUSIONS: BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.
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spelling pubmed-30981002011-05-20 Biana: a software framework for compiling biological interactions and analyzing networks Garcia-Garcia, Javier Guney, Emre Aragues, Ramon Planas-Iglesias, Joan Oliva, Baldo BMC Bioinformatics Software BACKGROUND: The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. RESULTS: We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. CONCLUSIONS: BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules. BioMed Central 2010-01-27 /pmc/articles/PMC3098100/ /pubmed/20105306 http://dx.doi.org/10.1186/1471-2105-11-56 Text en Copyright ©2010 Garcia-Garcia 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 Software
Garcia-Garcia, Javier
Guney, Emre
Aragues, Ramon
Planas-Iglesias, Joan
Oliva, Baldo
Biana: a software framework for compiling biological interactions and analyzing networks
title Biana: a software framework for compiling biological interactions and analyzing networks
title_full Biana: a software framework for compiling biological interactions and analyzing networks
title_fullStr Biana: a software framework for compiling biological interactions and analyzing networks
title_full_unstemmed Biana: a software framework for compiling biological interactions and analyzing networks
title_short Biana: a software framework for compiling biological interactions and analyzing networks
title_sort biana: a software framework for compiling biological interactions and analyzing networks
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3098100/
https://www.ncbi.nlm.nih.gov/pubmed/20105306
http://dx.doi.org/10.1186/1471-2105-11-56
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