Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes.
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| Title: | Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes. |
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| Authors: | Orsi M; Department of Chemistry, Biochemistry & Pharmaceutical Sciences, University of Bern, Freiestrasse 3, 3012, Bern, Switzerland., Shing Loh B; Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore, 117543, Singapore., Weng C; Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore, 117543, Singapore., Ang WH; Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore, 117543, Singapore.; NUS Graduate School - Integrated Science and Engineering Programme (ISEP), National University of Singapore, 21 Lower Kent Ridge Rd, Singapore, 119077, Singapore., Frei A; Department of Chemistry, Biochemistry & Pharmaceutical Sciences, University of Bern, Freiestrasse 3, 3012, Bern, Switzerland. |
| Source: | Angewandte Chemie (International ed. in English) [Angew Chem Int Ed Engl] 2024 Mar 04; Vol. 63 (10), pp. e202317901. Date of Electronic Publication: 2024 Jan 24. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Wiley-VCH Country of Publication: Germany NLM ID: 0370543 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1521-3773 (Electronic) Linking ISSN: 14337851 NLM ISO Abbreviation: Angew Chem Int Ed Engl Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1521-3773 |
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| DOI: | 10.1002/anie.202317901 |
