Data mining in the MetaCyc family of pathway databases

Area of Science:

• Systems Biology
• Bioinformatics
• Metabolic Engineering

Background:

• Pathway databases are crucial for understanding biological processes by cataloging bioreactions and molecular interactions.
• The MetaCyc family comprises thousands of pathway databases, computationally inferred from the MetaCyc pathway/genome database (PGDB) and often manually curated.
• Curated pathway databases are now available for most major model organisms, facilitating comparative and in-depth biological research.

Purpose of the Study:

• To present methods for performing data mining on the MetaCyc family of pathway databases.
• To detail the various data access mechanisms available for the MetaCyc database family.
• To introduce interactive data mining tools within Pathway Tools for omics data analysis.

Main Methods:

• Discussed major data access mechanisms, including data files in multiple formats.
• Detailed application programming interfaces (APIs) for Lisp, Java, and Perl languages.
• Presented an overview of the Pathway Tools schema and interactive data mining tools for omics analysis.

Main Results:

• Established multiple pathways for accessing and querying the MetaCyc pathway databases.
• Provided insights into the Pathway Tools software schema, essential for database querying.
• Highlighted interactive tools within Pathway Tools for advanced omics data analysis.

Conclusions:

• The MetaCyc family of pathway databases, managed by Pathway Tools, offers robust data mining capabilities.
• Diverse data access mechanisms and integrated tools facilitate comprehensive analysis of biological pathways and omics data.
• These resources are invaluable for researchers studying metabolic pathways and molecular interactions across various organisms.