Email updates

Keep up to date with the latest news and content from Source Code for Biology and Medicine and BioMed Central.

Open Access Research

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

Natapol Pornputtapong, Kwanjeera Wanichthanarak, Avlant Nilsson, Intawat Nookaew and Jens Nielsen

Author Affiliations

For all author emails, please log on.

Source Code for Biology and Medicine 2014, 9:17  doi:10.1186/1751-0473-9-17

Published: 10 July 2014

Abstract (provisional)

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.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.