SynTemp: Efficient Extraction of Graph-Based Reaction Rules from Large-Scale Reaction Databases.

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Title: SynTemp: Efficient Extraction of Graph-Based Reaction Rules from Large-Scale Reaction Databases.
Authors: Phan TL; Bioinformatics Group, Department of Computer Science &Interdisciplinary Center for Bioinformatics &School for Embedded and Composite Artificial Intelligence (SECAI), Leipzig University, Härtelstraße 16-18, D-04107 Leipzig, Germany.; Department of Mathematics and Computer Science, University of Southern Denmark, DK-5230 Odense M, Denmark., Weinbauer K; Bioinformatics Group, Department of Computer Science &Interdisciplinary Center for Bioinformatics &School for Embedded and Composite Artificial Intelligence (SECAI), Leipzig University, Härtelstraße 16-18, D-04107 Leipzig, Germany.; Machine Learning Research Unit, TU Wien Informatics, A-1040 Wien, Austria., Laffitte MEG; Bioinformatics Group, Department of Computer Science &Interdisciplinary Center for Bioinformatics &School for Embedded and Composite Artificial Intelligence (SECAI), Leipzig University, Härtelstraße 16-18, D-04107 Leipzig, Germany.; Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Leipzig University, D-04103 Leipzig, Germany., Pan Y; Department of Mathematics and Computer Science, University of Southern Denmark, DK-5230 Odense M, Denmark.; Department of Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Vienna, Austria., Merkle D; Department of Mathematics and Computer Science, University of Southern Denmark, DK-5230 Odense M, Denmark.; Faculty of Technology, Bielefeld University, Postfach 10 01 31, D-33501 Bielefeld, Germany., Andersen JL; Department of Mathematics and Computer Science, University of Southern Denmark, DK-5230 Odense M, Denmark., Fagerberg R; Department of Mathematics and Computer Science, University of Southern Denmark, DK-5230 Odense M, Denmark., Flamm C; Department of Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Vienna, Austria., Stadler PF; Bioinformatics Group, Department of Computer Science &Interdisciplinary Center for Bioinformatics &School for Embedded and Composite Artificial Intelligence (SECAI), Leipzig University, Härtelstraße 16-18, D-04107 Leipzig, Germany.; Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany.; Facultad de Ciencias, Universidad National de Colombia, Bogotá CO-111321, Colombia.; Center for non-coding RNA in Technology and Health, University of Copenhagen, Ridebanevej 9, DK-1870 Frederiksberg, Denmark.; Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, New Mexico 87501, United States.
Source: Journal of chemical information and modeling [J Chem Inf Model] 2025 Mar 24; Vol. 65 (6), pp. 2882-2896. Date of Electronic Publication: 2025 Feb 28.
Publication Type: Journal Article
Journal Info: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1549-960X
DOI:10.1021/acs.jcim.4c01795