Database and Visualization for Advanced Systems Biology

Doktorsavhandling, 2014

In the information age, there is plenty of information available publicly in the field of biology. Utilization of biological data is still slow and inefficient compared to the amount of data generated. This problem arise due to the specific characteristics of biological data, which are complex, dynamic and variable. With the introduction of high throughput technologies, the gap between data creation and utilization has become wider. This issue is critical and poses a challenge in the field of systems biology, where data from several sources are needed for model construction and analysis. In order to build a data ecosystem to support human tissue specific genome reconstruction and further analysis, a collection of libraries, applications and a web site have been developed. A dedicated database management system was designed specifically for metabolic and related data to support human tissue specific genome scale metabolic model reconstruction providing data standardization and data integration. Two database APIs, Corgi and Dactyls, were developed following the Object-oriented data model to fulfill the database management system’s functions. This database management system was used to manage, provide and exchange information concerning particularly human metabolism. Furthermore was developed the visualization system, Ondine that allows overlaying of data and information on metabolic pathway maps with a zoom/pan user interface. In order to efficiently deploy human tissue specific metabolic information from a collection of genome-scale metabolic models (GEMs), the Human Metabolic Atlas (HMA) website was created as an online resource to provide comprehensive human metabolic information as models and as a database for further specific analysis. In addition, the Atlas also serves as a tool for communicating with the wider research community. The Atlas, providing a visualization of the metabolic map implemented on the Ondine engine, provides comparative information of metabolism among deposited GEMs. Hreed is intended to provide accurate information about human metabolism in order to exchange data with the community and to support metabolic network based modeling and analysis through both the graphical and application programming interfaces. This data ecosystem development and implementation is the starting step for the enhancement of data utilization in systems biology.