Analysis and comparison of metabolic pathway databases.

Area of Science:

• Genomics
• Bioinformatics
• Systems Biology

Background:

• Genome sequencing generates vast data, yet 30-40% of identified genes lack functional annotation.
• This knowledge gap hinders a comprehensive understanding of organismal biological functions.
• Pathway databases integrate existing biochemical pathway knowledge and aid genomic data interpretation.

Purpose of the Study:

• To summarize and analyze existing pathway databases and associated biological databases.
• To evaluate the content, structure, data organization, and reliability of these databases.
• To provide guidance for biological scientists on utilizing pathway databases effectively.

Main Methods:

• Review and summarization of selected pathway databases and their linked biological databases.
• Analysis of database content, structural organization, and data reliability from a biological perspective.
• Examination of data representation methods and available tools for data manipulation.

Main Results:

• Identified limitations in current pathway databases, particularly the frequent lack of experimental data.
• Detailed the advantages and disadvantages of various analyzed pathway databases.
• Provided insights into data organization, reliability, and usability for biological research.

Conclusions:

• Pathway databases are valuable for functional genomics but require careful evaluation due to varying data quality and completeness.
• Enhanced integration of experimental data and standardized representation are crucial for improving pathway database utility.
• This review offers a practical overview to assist biologists in selecting and using appropriate pathway databases.