L2L

L2L identifies enrichment of Gene Ontology (GO) terms and shared differential-expression patterns by comparing user-provided lists of up- or down-regulated genes to a curated database of differentially expressed genes from published mammalian microarray studies.

Key Features:

• Curated DE gene database: Contains differentially expressed genes derived from hundreds of published mammalian microarray experiments.
• GO term enrichment analysis: Tests user-provided up- or down-regulated gene lists for significant enrichment in Gene Ontology (GO) terms.
• Cross-study comparison: Compares gene lists against published experiments to identify common patterns of gene regulation across studies.
• Disease-pattern detection: Facilitates identification of novel biological patterns in disease datasets, exemplified by re-analysis of diabetic nephropathy.

Scientific Applications:

• Functional interpretation of microarray data: Elucidates biological processes and pathways underlying lists of differentially expressed genes via GO enrichment.
• Meta-analysis of microarray experiments: Identifies shared expression signatures across published mammalian microarray studies.
• Disease mechanism discovery: Reveals disease-associated gene expression patterns, such as those observed in diabetic nephropathy.
• Hypothesis generation: Produces candidate biological processes and pathways for further experimental validation.

Methodology:

Compares user-supplied up- or down-regulated gene lists to a curated database of differentially expressed genes from published mammalian microarray experiments and performs statistical testing for Gene Ontology (GO) term enrichment.