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

Important notice:

The data are free to use for non-commercial, academic purposes, provided that the original source is
cited and the authors and the publication are credited in any derivative work.

A patent application has been filed for the method described by van Oosten and Klein, which uses mass
spectrometry and machine learning to identify the pharmacological or other effects of compounds on cell
cultures and other biological systems.

Therefore, a license for the commercial use of the method must be negotiated by contacting either

Anke Faller
Universität Heidelberg
Dezernat Forschung
Rechts- und Strukturfragen der Forschungsförderung
Seminarstraße 2, 69117 Heidelberg
Tel. [phone]
anke.faller(at)zuv.uni-heidelberg.de

or

Prof. Dr. C. Klein; c.klein(at)uni-heidelberg.de
Medicinal Chemistry
Institute of Pharmacy and Molecular Biotechnology IPMB
Heidelberg University, INF 364
D-69120 Heidelberg
Germany
Phone: ++49-6221-54-4875
FAX  : ++49-6221-54-6430