Julian Hoßbach

Deep Learning-Driven Peptide Classification in Biological Nanopores

This work translates the peptide identification problem into an image-classification task by transforming each resistive pulse into a scaleogram via the continuous wavelet transform, a representation that jointly encodes amplitude, frequency, and time in a form well suited for deep convolutional models.