An Information-based Model for an Interactive Web Service with Agricultural Biotechnology

The National Agricultural Biotechnology Information Center (NABIC) constructed an agricultural biology-based infrastructure and developed a biological information-based database. The major functions of the NABIC are focused on biotechnological developments for agricultural bioinformatics and providing a web-based service to construct bioinformatics workflows easily, such as protein function prediction and genome systems biology programs. The NABIC has concentrated on the functional genomics of major crops, building an integrated biotechnology database for agro-biotech information that focuses on the proteomics of major agricultural resources, such as rice, Chinese cabbage, rice Ds-tagging lines, and microorganisms.

A New Approach to Find Orthologous Proteins Using Sequence and Protein-Protein Interaction Similarity

Developed proteome-scale ortholog and paralog prediction methods are mainly based on sequence similarity. However, it is known that even the closest BLAST hit often does not mean the closest neighbor. For this reason, we added conserved interaction information to find orthologs. We propose a genome-scale, automated ortholog prediction method, named OrthoInterBlast. The method is based on both sequence and interaction similarity. When we applied this method to fly and yeast, 17% of the ortholog candidates were different compared with the results of Inparanoid. By adding protein-protein interaction information, proteins that have low sequence similarity still can be selected as orthologs, which can not be easily detected by sequence homology alone.

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

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.