r with expansion radius r = 0, 1, 2, . . . for each reaction i ∈ R. The collection of partial ITS graphs can be partitioned further into sets of unique reaction patterns by verifying isomorphisms (see Alg. A.1). Our clustering method does not employ machine learning but categorizes reaction centers based on isomorphism. For larger values of r, however, this becomes computationally demanding for larger datasets. We, therefore, make use of the fact that these partial ITS graphs of the extended reaction centers form a hierarchical structure as an immediate consequence of Cor. 1.