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Enzyme Annotation and Metabolic Reconstruction Using KEGG.
1Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-0011, Japan. kanehisa@kuicr.kyoto-u.ac.jp.
Methods in Molecular Biology (Clifton, N.J.)
|April 29, 2017
Summary
KEGG Orthology (KO) links gene sequences to biological functions. This study presents methods using KEGG tools like BlastKOALA for enzyme annotation and metabolic reconstruction.
Area of Science:
- Bioinformatics
- Systems Biology
- Genomics
Background:
- KEGG is a comprehensive database resource.
- It integrates sequence data with biological functions at multiple levels.
- KEGG Orthology (KO), PATHWAY, MODULE, and GENES databases store functional and genomic information.
Purpose of the Study:
- To present knowledge-based prediction methods for functional characterization of amino acid sequences.
- To demonstrate the utility of KEGG tools for biological data analysis.
Main Methods:
- Utilizing the KEGG resource for functional annotation.
- Employing BlastKOALA for sequence similarity searching against KEGG Orthology.
- Using KEGG Mapper for pathway and module reconstruction.
Main Results:
- Developed and presented methods for predicting biological functions from amino acid sequences.
- Demonstrated successful enzyme annotation using KEGG tools.
- Showcased the application of KEGG Mapper for metabolic reconstruction.
Conclusions:
- KEGG provides a robust framework for linking genomic information to functional insights.
- KEGG tools like BlastKOALA and KEGG Mapper are effective for functional characterization and metabolic pathway analysis.
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