Identification of the set of genes collectively causes a disease is an important problem, called gene selection problem. This study introduces two distinct approaches for gene selection in the context of biological diseases: the Ranked Variance (RV) method and Differential Gene Expression Based Simulated Annealing (DGESA). The RV method prioritizes genes based on their variance, offering an initial perspective on potential biomarkers. DGESA, on the other hand, employs simulated annealing, integrating differential gene expression data to refine gene selection further. Through a case study focused on Eosinophilic Esophagus (EoE) and other gastro-intestinal diseases, we compare and contrast the outcomes of both methods. Notably, we identify 10 common genes between RV and DGESA in EoE, highlighting their complementary nature. Validation analyses reveal that 13 out of 40 final genes identified by DGESA for EoE are corroborated by existing literature, indicating their biological relevance. Similarly, in Ulcerative Colitis (UC) and Crohn's Disease (CD), 8 and 7 genes, respectively, out of the final 40 genes identified exhibit confirmation in the literature. These findings underscore the efficacy of both RV and DGESA in elucidating molecular signatures associated with gastro-intestinal diseases, contributing to our understanding of their pathogenesis and potential therapeutic targets.

The authors have declared no competing interest.

This study did not receive any funding

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All data produced in the present study are available upon reasonable request to the authors