A dedicated database system for handling multi-level data in systems biology
Journal article, 2014

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.

Author

Natapol Pornputtapong

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Kwanjeera Wanichthanarak

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Avlant Nilsson

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Intawat Nookaew

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Jens B Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Source Code for Biology and Medicine

1751-0473 (ISSN)

Vol. 9 1 17

Subject Categories

Biological Sciences

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

Areas of Advance

Life Science Engineering (2010-2018)

DOI

10.1186/1751-0473-9-17

More information

Created

10/7/2017