(fig. ) simulating the presence of noise in experiments (fig. ). The noise (fig. ) is extracted by initially subtracting a randomly simulated signal (e.g., using the signal fitted with the model of a wrong AA) from the experiment. In the next step, using FFT, a threshold estimation is extracted by analyzing the power spectral density (PSD). The frequency zones of high amplitude of PSD, corresponding to well-determined frequency are considered signals while the rest of the frequencies with average amplitude are considered as the threshold that will be subtracted. This average noisy FFT components depend also in the SNR of the experimental signal. A detailed process of noise extraction is also shown in supporting information. Figure (c) shows the extracted signal, which corresponds 100% with the analytical model. In this way, we have shown that it is possible to retrieve the peptide signatures even with SNR < 10dB if the complete titration spectrum of pH can be accessed.