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Library of molecular associations: curating the complex molecular basis of liver diseases

BACKGROUND: Systems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. Although these data often cover genome wide expression, the validity of single microarray exp...

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Autores principales: Buchkremer, Stefan, Hendel, Jasmin, Krupp, Markus, Weinmann, Arndt, Schlamp, Kai, Maass, Thorsten, Staib, Frank, Galle, Peter R, Teufel, Andreas
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851601/
https://www.ncbi.nlm.nih.gov/pubmed/20302666
http://dx.doi.org/10.1186/1471-2164-11-189
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author Buchkremer, Stefan
Hendel, Jasmin
Krupp, Markus
Weinmann, Arndt
Schlamp, Kai
Maass, Thorsten
Staib, Frank
Galle, Peter R
Teufel, Andreas
author_facet Buchkremer, Stefan
Hendel, Jasmin
Krupp, Markus
Weinmann, Arndt
Schlamp, Kai
Maass, Thorsten
Staib, Frank
Galle, Peter R
Teufel, Andreas
author_sort Buchkremer, Stefan
collection PubMed
description BACKGROUND: Systems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. Although these data often cover genome wide expression, the validity of single microarray experiments remains questionable. However, for systems biology approaches addressing the interactions of molecular networks comprehensive but also highly validated data are necessary. RESULTS: We have therefore generated the first comprehensive database for published molecular associations in human liver diseases. It is based on PubMed published abstracts and aimed to close the gap between genome wide coverage of low validity from microarray data and individual highly validated data from PubMed. After an initial text mining process, the extracted abstracts were all manually validated to confirm content and potential genetic associations and may therefore be highly trusted. All data were stored in a publicly available database, Library of Molecular Associations http://www.medicalgenomics.org/databases/loma/news, currently holding approximately 1260 confirmed molecular associations for chronic liver diseases such as HCC, CCC, liver fibrosis, NASH/fatty liver disease, AIH, PBC, and PSC. We furthermore transformed these data into a powerful resource for molecular liver research by connecting them to multiple biomedical information resources. CONCLUSION: Together, this database is the first available database providing a comprehensive view and analysis options for published molecular associations on multiple liver diseases.
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spelling pubmed-28516012010-04-09 Library of molecular associations: curating the complex molecular basis of liver diseases Buchkremer, Stefan Hendel, Jasmin Krupp, Markus Weinmann, Arndt Schlamp, Kai Maass, Thorsten Staib, Frank Galle, Peter R Teufel, Andreas BMC Genomics Software BACKGROUND: Systems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. Although these data often cover genome wide expression, the validity of single microarray experiments remains questionable. However, for systems biology approaches addressing the interactions of molecular networks comprehensive but also highly validated data are necessary. RESULTS: We have therefore generated the first comprehensive database for published molecular associations in human liver diseases. It is based on PubMed published abstracts and aimed to close the gap between genome wide coverage of low validity from microarray data and individual highly validated data from PubMed. After an initial text mining process, the extracted abstracts were all manually validated to confirm content and potential genetic associations and may therefore be highly trusted. All data were stored in a publicly available database, Library of Molecular Associations http://www.medicalgenomics.org/databases/loma/news, currently holding approximately 1260 confirmed molecular associations for chronic liver diseases such as HCC, CCC, liver fibrosis, NASH/fatty liver disease, AIH, PBC, and PSC. We furthermore transformed these data into a powerful resource for molecular liver research by connecting them to multiple biomedical information resources. CONCLUSION: Together, this database is the first available database providing a comprehensive view and analysis options for published molecular associations on multiple liver diseases. BioMed Central 2010-03-20 /pmc/articles/PMC2851601/ /pubmed/20302666 http://dx.doi.org/10.1186/1471-2164-11-189 Text en Copyright ©2010 Buchkremer 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
Buchkremer, Stefan
Hendel, Jasmin
Krupp, Markus
Weinmann, Arndt
Schlamp, Kai
Maass, Thorsten
Staib, Frank
Galle, Peter R
Teufel, Andreas
Library of molecular associations: curating the complex molecular basis of liver diseases
title Library of molecular associations: curating the complex molecular basis of liver diseases
title_full Library of molecular associations: curating the complex molecular basis of liver diseases
title_fullStr Library of molecular associations: curating the complex molecular basis of liver diseases
title_full_unstemmed Library of molecular associations: curating the complex molecular basis of liver diseases
title_short Library of molecular associations: curating the complex molecular basis of liver diseases
title_sort library of molecular associations: curating the complex molecular basis of liver diseases
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851601/
https://www.ncbi.nlm.nih.gov/pubmed/20302666
http://dx.doi.org/10.1186/1471-2164-11-189
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