IMA: Identifying disease-related genes using MeSH terms and association rules

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Genes are crucial in disease development and pathogenesis.
• Identifying gene-disease relationships is vital for biological and medical research.
• Mutated or dysregulated genes significantly contribute to disease mechanisms.

Purpose of the Study:

• To develop and validate a novel method for identifying disease-related genes.
• To leverage Medical Subject Headings (MeSH) terms and association rules for gene discovery.
• To construct gene-gene interaction networks for enhanced disease gene identification.

Main Methods:

• Analysis of MeSH terms to identify potential disease-related genes.
• Extraction of gene-gene interactions using association rule mining.
• Integration of extracted interactions to build gene-gene networks.
• Application of the method to five major cancers: prostate, lung, breast, stomach, and colorectal.

Main Results:

• The proposed method successfully identified 20 candidate genes for each of the five studied cancers.
• The method demonstrated superior performance in identifying disease-related and candidate genes compared to existing approaches.
• A total of 34 important candidate genes with supporting evidence for disease association were presented.

Conclusions:

• The developed method provides a powerful tool for identifying disease-related genes.
• This approach enhances the understanding of gene involvement in cancer pathogenesis.
• The identified candidate genes warrant further investigation for potential diagnostic or therapeutic applications.