Ontology highlight
ABSTRACT:
SUBMITTER: Perez KL
PROVIDER: S-EPMC11326248 | biostudies-literature | 2024 Aug
REPOSITORIES: biostudies-literature
Pérez Kenneth López KL Jung Vicky V Chen Lexin L Huddleston Kate K Miranda-Quintana Ramón Alain RA
bioRxiv : the preprint server for biology 20240810
The widespread use of Machine Learning (ML) techniques in chemical applications has come with the pressing need to analyze extremely large molecular libraries. In particular, clustering remains one of the most common tools to dissect the chemical space. Unfortunately, most current approaches present unfavorable time and memory scaling, which makes them unsuitable to handle million- and billion-sized sets. Here, we propose to bypass these problems with a time- and memory-efficient clustering algo ...[more]