
Computational modeling of Pum-mediated regulation of mRNAs identifies informative features. Leave-one-out analysis of a linear regression model applied to six influential features of Pum repression, labeled on the x-axis. The information contributed to the model by each feature was quantified with the change in the Bayesian Information Criterion (ΔBIC), where the difference was calculated as BIC1 left out − BICfull model, resulting in a positive ΔBIC value for informative features in the model.










