KEGG

Definition

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a comprehensive database that provides information on biological systems, including metabolic pathways, diseases, and drug development. It serves as a critical resource for integrating and interpreting data in systems biology, particularly in the analysis of metabolic networks and pathways.

5 Must Know Facts For Your Next Test

1. KEGG provides tools for pathway mapping, allowing researchers to visualize and analyze complex biological processes and their interconnections.
2. It includes various databases, such as KEGG PATHWAY, which focuses on metabolic and regulatory pathways, and KEGG GENES, which contains genomic information.
3. KEGG is widely used in pathway analysis and enrichment tools to assess the significance of metabolomic data in the context of biological functions.
4. Researchers can use KEGG for metabolite identification by matching experimental data against the comprehensive lists of known metabolites and their associated pathways.
5. The integration of metabolomics and proteomics data with KEGG pathways helps in understanding how metabolic changes relate to protein expression and function.

Review Questions

• How does KEGG facilitate univariate and multivariate statistical analysis in metabolomics?
  • KEGG provides a structured database that researchers can use to correlate metabolomic data with specific pathways or biological functions. By mapping metabolites onto KEGG pathways, scientists can employ univariate and multivariate statistical analyses to identify significant changes or patterns within their data. This integration allows for a clearer understanding of how specific metabolites contribute to overall biological responses and conditions.
• Discuss the importance of KEGG in pathway analysis and enrichment tools.
  • KEGG plays a crucial role in pathway analysis and enrichment tools by offering detailed information on known biological pathways and their associated metabolites. Researchers utilize KEGG's extensive databases to perform enrichment analyses that identify which pathways are significantly affected in their datasets. This helps in interpreting complex omics data by linking changes in metabolites to specific biological functions, thereby facilitating deeper insights into underlying mechanisms of diseases or treatments.
• Evaluate the role of KEGG in metabolic network reconstruction and its implications for integrating metabolomics with proteomics.
  • KEGG is essential for metabolic network reconstruction as it provides comprehensive pathway maps that illustrate the interactions between different metabolites and enzymes. This information is invaluable when integrating metabolomics with proteomics since it allows researchers to contextualize changes in metabolite levels alongside protein expression profiles. By analyzing these relationships through KEGG pathways, scientists can gain insights into metabolic regulation, identify potential biomarkers, and understand the broader implications of biochemical interactions in health and disease.

Related terms

Metabolic Pathway:

A series of chemical reactions occurring within a cell that lead to the conversion of substrates into products, often involving enzymes and metabolites.

Gene Ontology: A framework for the representation of gene functions that provides consistent terminology across species, allowing for better understanding and analysis of biological processes.

Pathway Enrichment Analysis: A statistical method used to identify significant biological pathways that are over-represented in a given dataset, often used to interpret omics data.