dc.contributor.author | Lederer, Jonas | |
dc.contributor.author | Gastegger, Michael | |
dc.contributor.author | Schütt, Kristof T. | |
dc.contributor.author | Kampffmeyer, Michael Christian | |
dc.contributor.author | Müller, Klaus-Robert | |
dc.contributor.author | Unke, Oliver T. | |
dc.date.accessioned | 2023-12-05T10:25:33Z | |
dc.date.available | 2023-12-05T10:25:33Z | |
dc.date.created | 2023-10-18T11:32:54Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Physical Chemistry, Chemical Physics - PCCP. 2023, 25 (38), 26370-26379. | en_US |
dc.identifier.issn | 1463-9076 | |
dc.identifier.uri | https://hdl.handle.net/11250/3105997 | |
dc.description.abstract | In recent years, the prediction of quantum mechanical observables with machine learning methods has become increasingly popular. Message-passing neural networks (MPNNs) solve this task by constructing atomic representations, from which the properties of interest are predicted. Here, we introduce a method to automatically identify chemical moieties (molecular building blocks) from such representations, enabling a variety of applications beyond property prediction, which otherwise rely on expert knowledge. The required representation can either be provided by a pretrained MPNN, or be learned from scratch using only structural information. Beyond the data-driven design of molecular fingerprints, the versatility of our approach is demonstrated by enabling the selection of representative entries in chemical databases, the automatic construction of coarse-grained force fields, as well as the identification of reaction coordinates. | en_US |
dc.language.iso | eng | en_US |
dc.rights | Navngivelse-Ikkekommersiell 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/deed.no | * |
dc.title | Automatic identification of chemical moieties | en_US |
dc.title.alternative | Automatic identification of chemical moieties | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | publishedVersion | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |
dc.identifier.doi | 10.1039/d3cp03845a | |
dc.identifier.cristin | 2185846 | |
dc.source.journal | Physical Chemistry, Chemical Physics - PCCP | en_US |
dc.source.volume | 25 | en_US |
dc.source.issue | 38 | en_US |
dc.source.pagenumber | 26370-26379 | en_US |