Figure 1.

Impact of smoking on the nasal epithelium. (A) The principle of scoring the transcriptomics data onto biological network models. The activation/inhibition of biological entities is predicted based on differential gene expression. (B) The network perturbation amplitude is computed as a whole based on the predicted impact on the biological entities constituting the network model.³⁶ (C) Heatmap comparing the impact of smoking and smoking cessation on each network across the data sets. The color gradient of the network perturbation amplitude score is normalized to the maximum score per network. Only the network models that show a significant impact for at least one sample type comparing current smokers and never-smokers are shown. A network is considered significantly perturbed if the network perturbation amplitude score remains significant after accounting for the experimental variation and if the companion statistics O and K are significant (P < .05). The O and K statistics indicate the specificity of the score to the biology represented by each network. *Significant score with respect to the experimental variation and with significant O and K statistics. CS indicates current smoker; FS: former smoker; NPA, network perturbation amplitude; NS: never-smoker.