A Linear Model Based on Nine of the Original 62 Signals Recapitulates Experimental Data and Matches Full Model Performance

<p>Results from PLSR modeling show that a computational model based on six signals generates predicted values of cellular migration and proliferation that correlate strongly with those predicted by the full model and experimentally measured values. Experimental values of migration (A) or proliferation (B) are graphed along the ordinate, and full-model predictions (black) and reduced-model predictions (red) of migration (A) or proliferation (B) are given along the abscissa. R² values indicate the data's goodness of fit to the line y = x. Experimental error bars denote 95% confidence intervals for migration (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030004#s4" target="_blank">Methods</a>) and ± standard deviation for proliferation. All computational error bars are calculated from jack-knifing as a standard error.