Molecular set transformer: attending to the co-crystals in the Cambridge structural database

Vriza, Aikaterini ORCID: 0000-0002-5663-8703, Sovago, Ioana, Widdowson, Daniel, Kurlin, Vitaliy ORCID: 0000-0001-5328-5351, Wood, Peter A ORCID: 0000-0002-5239-2160 and Dyer, Matthew S ORCID: 0000-0002-4923-3003 (2022) Molecular set transformer: attending to the co-crystals in the Cambridge structural database. Digital Discovery, 1 (6). pp. 834-850.

Access the full-text of this item by clicking on the Open Access link.

Official URL: http://dx.doi.org/10.1039/d2dd00068g

Abstract

<jats:p>Molecular set transformer is a deep learning architecture for scoring molecular pairs found in co-crystals, whilst tackling the class imbalance problem observed on datasets that include only successful synthetic attempts.</jats:p>

Item Type:	Article
Divisions:	Faculty of Science and Engineering > School of Physical Sciences
Depositing User:	Symplectic Admin
Date Deposited:	22 Feb 2023 15:28
Last Modified:	14 Mar 2024 17:32
DOI:	10.1039/d2dd00068g
Open Access URL:	https://doi.org/10.1039/D2DD00068G
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3168559