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A multilevel data integration resource for breast cancer study
BACKGROUND: Breast cancer is one of the most common cancer types. Due to the complexity of this disease, it is important to face its study with an integrated and multilevel approach, from genes, transcripts and proteins to molecular networks, cell populations and tissues. According to the systems bi...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2900226/ https://www.ncbi.nlm.nih.gov/pubmed/20525248 http://dx.doi.org/10.1186/1752-0509-4-76 |
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author | Mosca, Ettore Alfieri, Roberta Merelli, Ivan Viti, Federica Calabria, Andrea Milanesi, Luciano |
author_facet | Mosca, Ettore Alfieri, Roberta Merelli, Ivan Viti, Federica Calabria, Andrea Milanesi, Luciano |
author_sort | Mosca, Ettore |
collection | PubMed |
description | BACKGROUND: Breast cancer is one of the most common cancer types. Due to the complexity of this disease, it is important to face its study with an integrated and multilevel approach, from genes, transcripts and proteins to molecular networks, cell populations and tissues. According to the systems biology perspective, the biological functions arise from complex networks: in this context, concepts like molecular pathways, protein-protein interactions (PPIs), mathematical models and ontologies play an important role for dissecting such complexity. RESULTS: In this work we present the Genes-to-Systems Breast Cancer (G2SBC) Database, a resource which integrates data about genes, transcripts and proteins reported in literature as altered in breast cancer cells. Beside the data integration, we provide an ontology based query system and analysis tools related to intracellular pathways, PPIs, protein structure and systems modelling, in order to facilitate the study of breast cancer using a multilevel perspective. The resource is available at the URL http://www.itb.cnr.it/breastcancer. CONCLUSIONS: The G2SBC Database represents a systems biology oriented data integration approach devoted to breast cancer. By means of the analysis capabilities provided by the web interface, it is possible to overcome the limits of reductionist resources, enabling predictions that can lead to new experiments. |
format | Text |
id | pubmed-2900226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29002262010-07-09 A multilevel data integration resource for breast cancer study Mosca, Ettore Alfieri, Roberta Merelli, Ivan Viti, Federica Calabria, Andrea Milanesi, Luciano BMC Syst Biol Database BACKGROUND: Breast cancer is one of the most common cancer types. Due to the complexity of this disease, it is important to face its study with an integrated and multilevel approach, from genes, transcripts and proteins to molecular networks, cell populations and tissues. According to the systems biology perspective, the biological functions arise from complex networks: in this context, concepts like molecular pathways, protein-protein interactions (PPIs), mathematical models and ontologies play an important role for dissecting such complexity. RESULTS: In this work we present the Genes-to-Systems Breast Cancer (G2SBC) Database, a resource which integrates data about genes, transcripts and proteins reported in literature as altered in breast cancer cells. Beside the data integration, we provide an ontology based query system and analysis tools related to intracellular pathways, PPIs, protein structure and systems modelling, in order to facilitate the study of breast cancer using a multilevel perspective. The resource is available at the URL http://www.itb.cnr.it/breastcancer. CONCLUSIONS: The G2SBC Database represents a systems biology oriented data integration approach devoted to breast cancer. By means of the analysis capabilities provided by the web interface, it is possible to overcome the limits of reductionist resources, enabling predictions that can lead to new experiments. BioMed Central 2010-06-03 /pmc/articles/PMC2900226/ /pubmed/20525248 http://dx.doi.org/10.1186/1752-0509-4-76 Text en Copyright ©2010 Mosca 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 | Database Mosca, Ettore Alfieri, Roberta Merelli, Ivan Viti, Federica Calabria, Andrea Milanesi, Luciano A multilevel data integration resource for breast cancer study |
title | A multilevel data integration resource for breast cancer study |
title_full | A multilevel data integration resource for breast cancer study |
title_fullStr | A multilevel data integration resource for breast cancer study |
title_full_unstemmed | A multilevel data integration resource for breast cancer study |
title_short | A multilevel data integration resource for breast cancer study |
title_sort | multilevel data integration resource for breast cancer study |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2900226/ https://www.ncbi.nlm.nih.gov/pubmed/20525248 http://dx.doi.org/10.1186/1752-0509-4-76 |
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