Sort & Slice: A Simple and Superior Alternative to Hash-Based Folding for Extended-Connectivity Fingerprints

arXiv:2403.17954v1 Announce Type: new
Abstract: Extended-connectivity fingerprints (ECFPs) are a ubiquitous tool in current cheminformatics and molecular machine learning, and one of the most prevalent molecular feature extraction techniques used for chemical prediction. Atom features learned by graph neural networks can be aggregated to compound-level representations using a large spectrum of graph pooling methods; in contrast, sets of detected ECFP substructures are by default transformed into bit vectors using only a simple hash-based folding procedure. We introduce a general mathematical …

abstract arxiv atom connectivity cs.lg current extraction feature feature extraction features fingerprints graph graph neural networks hash machine machine learning networks neural networks physics.chem-ph prediction q-bio.bm simple slice tool type