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A dedicated database system for handling multi-level data in systems biology

BACKGROUND: Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties...

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Autores principales: Pornputtapong, Natapol, Wanichthanarak, Kwanjeera, Nilsson, Avlant, Nookaew, Intawat, Nielsen, Jens
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106218/
https://www.ncbi.nlm.nih.gov/pubmed/25053973
http://dx.doi.org/10.1186/1751-0473-9-17
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author Pornputtapong, Natapol
Wanichthanarak, Kwanjeera
Nilsson, Avlant
Nookaew, Intawat
Nielsen, Jens
author_facet Pornputtapong, Natapol
Wanichthanarak, Kwanjeera
Nilsson, Avlant
Nookaew, Intawat
Nielsen, Jens
author_sort Pornputtapong, Natapol
collection PubMed
description BACKGROUND: Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties in data accessibility and often results in errors when data are merged and integrated from varied resources. Therefore, integration and management of systems biological data remain very challenging. METHODS: To overcome this, we designed and developed a dedicated database system that can serve and solve the vital issues in data management and hereby facilitate data integration, modeling and analysis in systems biology within a sole database. In addition, a yeast data repository was implemented as an integrated database environment which is operated by the database system. Two applications were implemented to demonstrate extensibility and utilization of the system. Both illustrate how the user can access the database via the web query function and implemented scripts. These scripts are specific for two sample cases: 1) Detecting the pheromone pathway in protein interaction networks; and 2) Finding metabolic reactions regulated by Snf1 kinase. RESULTS AND CONCLUSION: In this study we present the design of database system which offers an extensible environment to efficiently capture the majority of biological entities and relations encountered in systems biology. Critical functions and control processes were designed and implemented to ensure consistent, efficient, secure and reliable transactions. The two sample cases on the yeast integrated data clearly demonstrate the value of a sole database environment for systems biology research.
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spelling pubmed-41062182014-07-23 A dedicated database system for handling multi-level data in systems biology Pornputtapong, Natapol Wanichthanarak, Kwanjeera Nilsson, Avlant Nookaew, Intawat Nielsen, Jens Source Code Biol Med Research BACKGROUND: Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties in data accessibility and often results in errors when data are merged and integrated from varied resources. Therefore, integration and management of systems biological data remain very challenging. METHODS: To overcome this, we designed and developed a dedicated database system that can serve and solve the vital issues in data management and hereby facilitate data integration, modeling and analysis in systems biology within a sole database. In addition, a yeast data repository was implemented as an integrated database environment which is operated by the database system. Two applications were implemented to demonstrate extensibility and utilization of the system. Both illustrate how the user can access the database via the web query function and implemented scripts. These scripts are specific for two sample cases: 1) Detecting the pheromone pathway in protein interaction networks; and 2) Finding metabolic reactions regulated by Snf1 kinase. RESULTS AND CONCLUSION: In this study we present the design of database system which offers an extensible environment to efficiently capture the majority of biological entities and relations encountered in systems biology. Critical functions and control processes were designed and implemented to ensure consistent, efficient, secure and reliable transactions. The two sample cases on the yeast integrated data clearly demonstrate the value of a sole database environment for systems biology research. BioMed Central 2014-07-10 /pmc/articles/PMC4106218/ /pubmed/25053973 http://dx.doi.org/10.1186/1751-0473-9-17 Text en Copyright © 2014 Pornputtapong et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Pornputtapong, Natapol
Wanichthanarak, Kwanjeera
Nilsson, Avlant
Nookaew, Intawat
Nielsen, Jens
A dedicated database system for handling multi-level data in systems biology
title A dedicated database system for handling multi-level data in systems biology
title_full A dedicated database system for handling multi-level data in systems biology
title_fullStr A dedicated database system for handling multi-level data in systems biology
title_full_unstemmed A dedicated database system for handling multi-level data in systems biology
title_short A dedicated database system for handling multi-level data in systems biology
title_sort dedicated database system for handling multi-level data in systems biology
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106218/
https://www.ncbi.nlm.nih.gov/pubmed/25053973
http://dx.doi.org/10.1186/1751-0473-9-17
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