Online tutorial on survival analysis for biomarker discovery.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 41860996.
- Also identified by DOI 10.1371/journal.pcbi.1014046 and PMC identifier 13004506.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
In 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.
Medical subject headings
- Biomarkers
- Computational Biology