20.500.12556/RUL-169617 Large scale gene set ranking for survival-related gene sets Disease progression is closely linked to shifts in the expression levels of specific genes within molecular pathways. While gene set enrichment analysis is a widely employed method for identifying key disease markers, it has been underutilized in survival analysis. Here, we introduce a novel computational approach that adapts gene set enrichment analysis for survival analysis. The proposed approach considers a gene set, computes a single-sample gene set enrichment score, and, based on this score, splits the samples into cohorts. It then scores the gene sets by evaluating the differences in survival rates between the resulting cohorts. We aim to find gene sets that can lead to cohorts with significantly different survival probabilities. Utilizing gene expression data from The Cancer Genome Atlas and gene sets from the Molecular Signature Database, our results demonstrate that existing empirical research consistently supports the top gene sets our approach associates with survival prognosis. The proposed method broadens gene set enrichment analysis applications to include information on survival, bridging the gap between alterations in molecular pathways and their implications on survival. gene set ranking survival analysis censored data survival curve gene expression single-sample gene set enrichment scoring genetika genomi onkologija razvrščanje genov analiza preživetja krivulja preživetja markerji bolezni dejavniki tveganja true false true Angleški jezik Slovenski jezik Članek v reviji 2025-06-06 09:38:58 2025-06-06 09:39:00 2025-06-08 04:25:33 0000-00-00 00:00:00 2025 0 0 10 str. Vol. 167, art. 103149 Sep. 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 616-006:575 1873-2860 10.1016/j.artmed.2025.103149 238507011 1-s2.0-S0933365725000843-main.pdf 1-s2.0-S0933365725000843-main.pdf 1 D194321A5C28FA52FA23EED50A51EE77 2ea771704f78ecd8459bd115a2e70f3d174dea4aa1d1e9ca980395f6993a570e 404aa98f-42a8-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=211126 https://www.sciencedirect.com/science/article/pii/S0933365725000843 0 fda27d2e-42a7-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=211125 Fakulteta za računalništvo in informatiko 0 0 0