Machine learning in mass spectrometry: A MALDI-TOF MS approach to phenotypic antibacterial screening

Dataset relating to the publication: Machine learning in mass spectrometry: A MALDI-TOF MS approach to phenotypic antibacterial screening by Luuk Nico van Oosten and Christian D. Klein Published in the Journal of Medicinal Chemistry, 2020 <strong>Important notice:</strong> <strong>The data are free to use for non-commercial, academic purposes, provided that the original source is<br> cited and the authors and the publication are credited in any derivative work.</strong> <strong>A patent application has been filed for the method described by van Oosten and Klein, which uses mass<br> spectrometry and machine learning to identify the pharmacological or other effects of compounds on cell<br> cultures and other biological systems.</strong> Therefore, a license for the commercial use of the method must be negotiated by contacting either Anke Faller<br> Universität Heidelberg<br> Dezernat Forschung<br> Rechts- und Strukturfragen der Forschungsförderung<br> Seminarstraße 2, 69117 Heidelberg<br> Tel. [phone]<br> anke.faller(at)zuv.uni-heidelberg.de or Prof. Dr. C. Klein; c.klein(at)uni-heidelberg.de<br> Medicinal Chemistry<br> Institute of Pharmacy and Molecular Biotechnology IPMB<br> Heidelberg University, INF 364<br> D-69120 Heidelberg<br> Germany<br> Phone: ++49-6221-54-4875<br> FAX : ++49-6221-54-6430