geneRecommender

geneRecommender identifies genes with similar functions by analyzing whole-genome microarray expression data to find genes coexpressed with a predefined set of query genes.

Key Features:

• Targeted Clustering Algorithm: Employs a targeted clustering approach tailored for microarray data to prioritize genes with expression patterns related to the query gene set.
• Correlation-Based Ranking: Ranks candidate genes by evaluating correlation with the query genes specifically in experiments where those query genes exhibit strong coregulation.
• Precision and Recall Optimization: Produces candidate gene lists optimized for higher precision at fixed levels of recall compared to methods such as the C. elegans expression topomap.

Scientific Applications:

• Gene Function Discovery: Aids identification of novel genes that may share functional roles with known genes through coexpression analysis.
• Functional Genomics Research: Supports studies to elucidate gene networks, pathways, and genes involved in specific cellular functions or disease mechanisms.
• Cancer and Retinoblastoma Complex Studies: Has been applied to identify genes coexpressed with retinoblastoma complex components, including identification of JC8.6 as functioning with lin-35 Rb and WRM-1 as an antagonistic factor.

Methodology:

Analyzes whole-genome microarray expression data using a targeted clustering algorithm, focuses on experiments where the query genes show strong coregulation, ranks genes by correlation to the query set, and selects lists optimized for precision at fixed recall levels.