Fig. 1: Cancer cell line classification algorithm and gene dependency modeling strategies.
From: Diffusion kernel-based predictive modeling of KRAS dependency in KRAS wild type cancer cell lines
a Strategy of cell line subgrouping leading to the investigated subgroups (HRASwt/HRASmut, KRASwt/KRASmut, NRASwt/NRASmut). b Variable selection workflow for whole transcriptome RNA-expression data consisting of the construction of a literature-based gene network followed by further selections steps with centrality quantification through a diffusion kernel and a minimum required expression level. Several different constellations of the hyperparameters were tested. Final modeling was performed using a Lasso, Elastic Net or Random Forest regression. c Workflow of iterative model fitting and performance evaluation for each gene dependency dataset.
