Fig. 1. Schematic overview of the learned model described in this paper. Each glycan is decomposed into a fingerprint of feature counts, primarily of small q-gram subtrees (here q = 1, 2, or 3). This fingerprint is then input into the learned model which outputs the predicted binding value between the glycan and each of the 1257 protein samples.