2 papers
stat.ME2026
PliableBVS: A flexible Bayesian variable selection method for modeling interactions with mandatory modifying variables
Theophilus Quachie Asenso, Zhi Zhao, Maren-Helene Langeland Degnes +3
High-dimensional interaction models are useful for studying, for example, how a large set of variables of interest, such as gene expression or other omics features, interact with a…
stat.ME2025
Bayesian Cox model with graph-structured variable selection priors for multi-omics biomarker identification
Tobias Ãstmo Hermansen, Manuela Zucknick, Zhi Zhao
An important goal in cancer research is the survival prognosis of a patient based on a minimal panel of genomic and molecular markers such as genes or proteins. Purely data-driven…