Genomics Inform.  2004 Dec;2(4):191-194.

The BIOWAY System: A Data Warehouse for Generalized Representation & Visualization of Bio-Pathways

Affiliations
  • 1Department of Computer Science and Engineering,Ewha University, Seoul 120-750, Korea.
  • 2Department of Institute of Bioinformatics, Macrogen Inc., Seoul 153-023, Korea.
  • 3School of Computer Engineering, Sejong University,Seoul 143-747, Korea.

Abstract

Exponentially increasing biopathway data in recent years provide us with means to elucidate the large-scale modular organization of the cell. Given the existing information on metabolic and regulatory networks, inferring biopathway information through scientific reasoning or data mining of large scale array data or proteomics data get great attention. Naturally, there is a need for a user-friendly system allowing the user to combine large and diverse pathway data sets from different resources. We built a data warehouse - BIOWAY - for analyzing and visualizing biological pathways, by integrating and customizing resources. We have collected many different types of data in regards to pathway information,including metabolic pathway data from KEGG/LIGAND,signaling pathway data from BIND, and protein information data from SWISS-PROT.In addition to providing general data retrieval mechanism, a successful user interface should provide convenient visualization mechanism since biological pathway data is difficult to conceptualize without graphical representations. Still, the visual interface in the previous systems, at best, uses static images only for the specific categorized pathways. Thus, it is difficult to cope with more complex pathways. In the BIOWAY system, all the pathway data can be displayed in computer generated graphical networks, rather than manually drawn image data. Furthermore, it is designed in such a way that all the pathway maps can be expanded or shrinked, by introducing the concept of super node. A subtle graphic layout algorithm has been applied to best display the pathway data.


MeSH Terms

Data Mining
Dataset
Information Storage and Retrieval
Metabolic Networks and Pathways
Proteomics
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