Cargando…

Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies

BACKGROUND: This paper summarises the lessons and experiences gained from a case study of the application of semantic web technologies to the integration of data from the bacterial species Francisella tularensis novicida (Fn). Fn data sources are disparate and heterogeneous, as multiple laboratories...

Descripción completa

Detalles Bibliográficos
Autores principales: Anwar, Nadia, Hunt, Ela
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2755824/
https://www.ncbi.nlm.nih.gov/pubmed/19796400
http://dx.doi.org/10.1186/1471-2105-10-S10-S3
_version_ 1782172473282789376
author Anwar, Nadia
Hunt, Ela
author_facet Anwar, Nadia
Hunt, Ela
author_sort Anwar, Nadia
collection PubMed
description BACKGROUND: This paper summarises the lessons and experiences gained from a case study of the application of semantic web technologies to the integration of data from the bacterial species Francisella tularensis novicida (Fn). Fn data sources are disparate and heterogeneous, as multiple laboratories across the world, using multiple technologies, perform experiments to understand the mechanism of virulence. It is hard to integrate these data sources in a flexible manner that allows new experimental data to be added and compared when required. RESULTS: Public domain data sources were combined in RDF. Using this connected graph of database cross references, we extended the annotations of an experimental data set by superimposing onto it the annotation graph. Identifiers used in the experimental data automatically resolved and the data acquired annotations in the rest of the RDF graph. This happened without the expensive manual annotation that would normally be required to produce these links. This graph of resolved identifiers was then used to combine two experimental data sets, a proteomics experiment and a transcriptomic experiment studying the mechanism of virulence through the comparison of wildtype Fn with an avirulent mutant strain. CONCLUSION: We produced a graph of Fn cross references which enabled the combination of two experimental datasets. Through combination of these data we are able to perform queries that compare the results of the two experiments. We found that data are easily combined in RDF and that experimental results are easily compared when the data are integrated. We conclude that semantic data integration offers a convenient, simple and flexible solution to the integration of published and unpublished experimental data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-10-S10-S3) contains supplementary material, which is available to authorized users.
format Text
id pubmed-2755824
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-27558242009-10-03 Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies Anwar, Nadia Hunt, Ela BMC Bioinformatics Research BACKGROUND: This paper summarises the lessons and experiences gained from a case study of the application of semantic web technologies to the integration of data from the bacterial species Francisella tularensis novicida (Fn). Fn data sources are disparate and heterogeneous, as multiple laboratories across the world, using multiple technologies, perform experiments to understand the mechanism of virulence. It is hard to integrate these data sources in a flexible manner that allows new experimental data to be added and compared when required. RESULTS: Public domain data sources were combined in RDF. Using this connected graph of database cross references, we extended the annotations of an experimental data set by superimposing onto it the annotation graph. Identifiers used in the experimental data automatically resolved and the data acquired annotations in the rest of the RDF graph. This happened without the expensive manual annotation that would normally be required to produce these links. This graph of resolved identifiers was then used to combine two experimental data sets, a proteomics experiment and a transcriptomic experiment studying the mechanism of virulence through the comparison of wildtype Fn with an avirulent mutant strain. CONCLUSION: We produced a graph of Fn cross references which enabled the combination of two experimental datasets. Through combination of these data we are able to perform queries that compare the results of the two experiments. We found that data are easily combined in RDF and that experimental results are easily compared when the data are integrated. We conclude that semantic data integration offers a convenient, simple and flexible solution to the integration of published and unpublished experimental data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-10-S10-S3) contains supplementary material, which is available to authorized users. BioMed Central 2009-10-01 /pmc/articles/PMC2755824/ /pubmed/19796400 http://dx.doi.org/10.1186/1471-2105-10-S10-S3 Text en © Anwar and Hunt; licensee BioMed Central Ltd. 2009 https://creativecommons.org/licenses/by/2.0/This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Anwar, Nadia
Hunt, Ela
Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies
title Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies
title_full Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies
title_fullStr Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies
title_full_unstemmed Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies
title_short Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies
title_sort francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2755824/
https://www.ncbi.nlm.nih.gov/pubmed/19796400
http://dx.doi.org/10.1186/1471-2105-10-S10-S3
work_keys_str_mv AT anwarnadia francisellatularensisnovicidaproteomicandtranscriptomicdataintegrationandannotationbasedonsemanticwebtechnologies
AT huntela francisellatularensisnovicidaproteomicandtranscriptomicdataintegrationandannotationbasedonsemanticwebtechnologies