Prognostic biomarker discovery in pancreatic cancer through hybrid ensemble feature selection and multi-omics data

John Zobolas; Anne-Marie George; Alberto López; Sebastian Fischer; Marc Becker; Tero Aittokallio

doi:10.1186/s13040-026-00546-0

Prognostic biomarker discovery in pancreatic cancer through hybrid ensemble feature selection and multi-omics data

BioData Min. 2026 Apr 9. doi: 10.1186/s13040-026-00546-0. Online ahead of print.

Authors

John Zobolas^{1

2}, Anne-Marie George³, Alberto López⁴, Sebastian Fischer^{5

6}, Marc Becker^{5

6}, Tero Aittokallio^{7

4

8

9}

Affiliations

¹ Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway. bblodfon@gmail.com.
² Oslo Centre for Biostatistics and Epidemiology (OCBE), Department of Biostatistics, University of Oslo, Oslo, Norway. bblodfon@gmail.com.
³ Department of Informatics, University of Oslo, Oslo, Norway.
⁴ Oslo Centre for Biostatistics and Epidemiology (OCBE), Department of Biostatistics, University of Oslo, Oslo, Norway.
⁵ Department of Statistics, Ludwig Maximilian University of Munich, Munich, Germany.
⁶ Munich Center for Machine Learning (MCML), Munich, Germany.
⁷ Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
⁸ Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
⁹ ICAN Digital Precision Cancer Medicine Flagship, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

PMID: 41957754
DOI: 10.1186/s13040-026-00546-0

No abstract available

Keywords: Biomarker discovery; Ensemble learning; Feature selection; High-dimensional data; Machine learning; Pareto optimization; Stability analysis; Survival analysis.