Analysis of gene ontology features in microarray data using the Proteome BioKnowledge Library

Area of Science:

• Bioinformatics
• Genomics
• Molecular Biology

Background:

• Microarray technology generates vast amounts of complex biological data.
• Efficient analysis requires integrating data with comprehensive databases to identify gene properties.
• Existing databases have limitations in effectively analyzing this complex data.

Purpose of the Study:

• To compare the utility of different databases for analyzing microarray data.
• To assess the effectiveness of the Proteome BioKnowledge Library (BKL) for identifying cardiovascular disease-related genes.
• To evaluate BKL's Gene Ontology (GO) and Disease annotations in microarray analysis.

Main Methods:

• Utilized the Proteome BioKnowledge Library (BKL) for curated scientific literature compilation.
• Generated Gene Ontology (GO) Biological Process (BP) terms enriched in cardiovascular disease proteins.
• Analyzed rat vascular smooth muscle cell microarray data and compared results with LocusLink and Gene Expression Omnibus (GEO) annotations.
• Generated orthologous gene sets for mouse and human using BKL Retriever and analyzed BKL Disease annotation.

Main Results:

• Microarray data analysis revealed significant enrichment of GO BPs also found in cardiovascular disease-related proteins.
• BKL database yielded more enriched cardiovascular disease-associated GO BP terms compared to LocusLink and GEO.
• Analysis of orthologous gene sets showed a significant association with cardiovascular disease using BKL Disease annotation.

Conclusions:

• The Proteome BioKnowledge Library (BKL) is a beneficial database for microarray analysis.
• BKL's curated GO and Disease annotations provide valuable insights into gene function and disease association.
• BKL demonstrates superior utility in identifying cardiovascular disease-related genes from complex microarray datasets.