Figure 1

Increased entropy in liver cancer is driven by increased entropy athubs:

(A) Boxplots comparing the entropy rate (SR) of 50 normal liver samples (N)to 50 matched liver cancer specimens (C), derived from RNA-Seq data of theTCGA consortium. P-value is from a one-tailed Wilcoxon rank sum test,testing the hypothesis that entropy rate is higher in cancer. Also shown isthe SR between normal and liver cancer for a case where the gene expressionprofiles were randomly permuted (perm) over the interaction network. Observehow the difference in the SR between normal and cancer is reduced and eventakes an opposite directionality, demonstrating that the interplay betweengene expression changes and network topology is dictating the highersignaling entropy in cancer. (B) Boxplots showing the change in the meanlocal entropy rate (LSR)(〈π_iLS_i〉_C−〈π_iLS_i〉_N)between normal and cancer of each node (gene) as a function of node degree,positive values indicating higher values in cancer. (C) Scatterplot of thedifferential change in the mean local entropy rate against the differentialchange in the mean invariant measure (INVP)(〈π_i〉_C−〈π_i〉_N).Each data point is one node (gene). (D) Boxplots showing the change in themean local entropy (LS) of each node (gene)(〈LS_i〉_C−〈LS_i〉_N)between normal and cancer, as a function of node degree.