20.500.12556/RUL-181155 Visual analytics framework for survival analysis and biomarker discovery from gene expression data We introduce a visual analytics methodology for survival analysis, and propose a framework that defines a reusable set of visualization and modeling components to support exploratory and hypothesis-driven biomarker discovery. Survival analysis—essential in biomedicine—evaluates patients‘ survival rates and the onset of medically relevant events, given their clinical and genetic profiles and genetic predispositions. Existing approaches often require programming expertise or rely on inflexible analysis pipelines, limiting their usability among biomedical researchers. The lack of advanced, user-friendly tools hinders problem solving, limits accessibility for biomedical researchers, and restricts interactive data exploration. Our methodology emphasizes functionality-driven design and modularity, akin to combining LEGO bricks to build tailored visual workflows. We (1) define a minimal set of reusable visualization and modeling components that support common survival analysis tasks, (2) implement interactive visualizations for discovering survival cohorts and their characteristic features, and (3) demonstrate integration within an existing visual analytics platform. We implemented the methodology as an open-source add-on to Orange Data Mining and validated it through use cases ranging from Kaplan–Meier estimation to biomarker discovery. While the framework is generally applicable, we illustrate its value through case studies in cancer research, where survival analysis is of critical importance. The resulting framework illustrates how methodological design can drive intuitive, transparent, and effective survival analysis. survival analysis visual analytics biomarker discovery gene expression data data analysis workflows analiza preživetja vizualna analitika odkrivanje biomarkerjev podatki o izražanju genov true false true Angleški jezik Slovenski jezik Članek v reviji 2026-03-26 10:11:37 2026-03-26 10:11:38 2026-03-30 04:15:05 0000-00-00 00:00:00 2026 0 0 19 str. iss. 3, art. e0325399 Vol. 21 2026 0000-00-00 Zaloznikova Objavljeno apc 0000-00-00 0000-00-00 0000-00-00 004:57 1932-6203 10.1371/journal.pone.0325399 273102339 RAZ_Kokosar_Jaka_2026.pdf RAZ_Kokosar_Jaka_2026.pdf 1 942C5A9A77895548D5543F0DAB70DF05 d17180ed9c27b3a4c9d1bbe82c3c992ef40225404ff28b250f814116e2444ab8 c2e3cc6c-28f4-11f1-b0ab-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=231364 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0325399 1 aaaec61c-28f3-11f1-b0ab-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=231361 Fakulteta za računalništvo in informatiko 0 0 0