Online tutorial on survival analysis for biomarker discoveryKokošar, Jaka (Avtor) Praznik, Ela (Avtor) Špendl, Martin (Avtor) Moreno, Nancy P. (Avtor) Newel, Alana (Avtor) Shaulsky, Gad (Avtor) Zupan, Blaž (Avtor) survival analysisbiomarker discoveryKaplan-Meier curvecensoringeducation and trainingIn biomedicine, survival analysis addresses time-to-event data to study outcomes like patient survival and treatment response, and supports biomarker discovery. Yet, teaching this analysis is often hindered by mathematical and programming barriers. We present a structured, hands-on tutorial that goes beyond a typical online guide—offering integrated video lectures, literature, quizzes, and practical exercises. Built around Orange Data Mining, an open and free no-code visual analytics platform, the tutorial covers key concepts such as censoring, Kaplan-Meier curves, group comparisons, and biomarker discovery through real-world datasets. Organized in four pedagogical units, it progresses from basic survival data analysis to gene and gene-set biomarker discovery. Designed for 2–3 hours of learning, it supports both individual study and classroom use, and was successfully tested with over 120 participants.20262026-03-26 10:43:32Članek v reviji181157sl