Visual analytics framework for survival analysis and biomarker discovery from gene expression data

Kokošar, Jaka (author), Turkay, Cagatay (author), Ausec, Luka (author), Štajdohar, Miha (author), Zupan, Blaž (author)

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.

• Language: English
• Keywords: survival analysis, visual analytics, biomarker discovery, gene expression data, data analysis workflows
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science
• Publication status: Published
• Publication version: Version of Record
• Year: 2026
• Number of pages: 19 str.
• Numbering: Vol. 21, iss. 3, art. e0325399
• PID: 20.500.12556/RUL-181155
• UDC: 004:57
• ISSN on article: 1932-6203
• DOI: 10.1371/journal.pone.0325399
• COBISS.SI-ID: 273102339
• Publication date in RUL: 26.03.2026

Record is a part of a journal

• Title: PloS one
• Publisher: Public Library of Science
• ISSN: 1932-6203
• COBISS.SI-ID: 2005896

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: analiza preživetja, vizualna analitika, odkrivanje biomarkerjev, podatki o izražanju genov