Figure 3

Simulated signal intensities and assigned amino acid-associated weights are recovered by an amino acid composition-based regression model. (A) Simulated signal intensities (${\overrightarrow{s}}_{\mathsf{\text{sim}}}$) obtained by amino acid position-dependent simulation of the binding of 150 antibodies to an array of 255 14-mer peptides were predicted using the regression model given by Equation 1. This regression model takes into account only the amino acid composition of the simulated peptide sequences. Predictive performance: Q² = 0.40. Simulated signal intensities were computed using Equation 2. (B) Equation 1 was used to estimate (${\overrightarrow{w}}_{\mathsf{\text{sim}}}$), which are shown against the assigned AAWS ($\overrightarrow{h}$) used to generate the simulated signal intensities ${\overrightarrow{s}}_{\mathsf{\text{sim}}}$. Coefficient of correlation: r = 0.92.