KEGG mapping tools for uncovering hidden features in biological data

Area of Science:

• Bioinformatics
• Systems Biology
• Genomics

Background:

• KEGG pathway maps are manually curated knowledge models of biological systems.
• These models facilitate biological big data analysis, such as KEGG mapping for genome interpretation.
• Previous versions of KEGG Mapper provided essential tools for these analyses.

Purpose of the Study:

• To present an updated version of KEGG Mapper with enhanced pathway and hierarchy viewers.
• To introduce new features for manipulating hierarchical trees in BRITE and taxonomy mapping.
• To improve the analysis of biological big data using KEGG models.

Main Methods:

• Updating KEGG Mapper tools, including pathway map and BRITE hierarchy viewers.
• Implementing tree manipulation features (pruning, zooming) for BRITE mapping.
• Integrating tree manipulation into the taxonomy mapping tool for KO groups and phenotype linkage.

Main Results:

• Enhanced KEGG Mapper suite with improved visualization and interaction.
• New functionalities for manipulating hierarchical data structures in BRITE and taxonomy mapping.
• Streamlined analysis of genomic data and functional annotation through updated KEGG mapping tools.

Conclusions:

• The updated KEGG Mapper offers advanced capabilities for biological data analysis.
• Enhanced visualization and manipulation tools facilitate deeper insights into biological systems.
• KEGG continues to leverage human intelligence for creating valuable biological models.