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The Extraction of Simple Relationships in Growth Factor-Specific Multiple-Input and Multiple-Output Systems in Cell-Fate Decisions by Backward Elimination PLS Regression

Figure 2

Construction of the PLS model.

(A) Construction of the PLS model. Inputs matrix X (20×60) regressed against the outputs matrix Y (20×95). Each column and row in X correspond with time course points of MAPKs and CREB, and the doses of stimuli, respectively. Each column and row in Y correspond with time course points of the IEGs and phenotypes, and with doses of stimuli, respectively. B is the coefficient matrix and E is the residue matrix of the PLS model. (B) LOOCV MSE (leave-one-out cross validation mean square error) as a function of the number of principal components. (C) The cumulative contribution percentage of the principal components. (D) Correlation plots between the measured and predicted outputs. The Pearson correlation coefficient, r, was 0.94. Each dot represents a single time point for one of the outputs.

Figure 2

doi: https://doi.org/10.1371/journal.pone.0072780.g002