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Dataset . 2016
License: CC BY NC
Data sources: Datacite
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A MALDI-TOF Mass Spectrometry Database for Identification and Classification of Highly Pathogenic Microorganisms from the Robert Koch-Institute (RKI)

Authors: Lasch, Peter; Stämmler, Maren; Schneider, Andy;

A MALDI-TOF Mass Spectrometry Database for Identification and Classification of Highly Pathogenic Microorganisms from the Robert Koch-Institute (RKI)

Abstract

(Version 20161027) Edit #1 (May 23, 2017): New database version (v.2 - 20170523) - available: 10.5281/zenodo.582602 Edit #2 (Nov 30, 2018): New database version (v.3 - 20181130) - available: 10.5281/zenodo.1880975 Edit #3 (Mar 06, 2023): New database version (v.4.2 - 20230306) - available: 10.5281/zenodo.7702375 The Robert Koch-Institute (RKI) database of microbial MALDI-TOF mass spectra contains mass spectral entries from highly pathogenic (biosafety level 3, BSL-3) bacteria such as Bacillus anthracis, Yersinia pestis, Burkholderia mallei, Burkholderia pseudomallei and Francisella tularensis as well as a selection of spectra from their close and more distant relatives. The RKI mass spectral database can be used as a reference for the diagnostics of BSL-3 bacteria using proprietary and free software packages for MALDI-TOF MS-based microbial identification. The database itself is distributed as a zip archive that contains the original mass spectra in its native data format (Bruker Daltonics). Please refer to the pdf file (161027-ZENODO-Metadata.pdf) to obtain information on the metadata of the spectra. Do not try to print this document (~1000 pages!) The pkf-file (161027_zenodo_Peaklist_(30Peaks1,6).pkf ) contains so-called database spectra in a Matlab compatible format. The latter data file can be imported into MicrobeMS, a Matlab-based free-of-charge software solution developed at the RKI. MicrobeMS is available from http://www.microbe-ms.com. For the future it is intended to update the RKI database of MALDI-TOF mass spectra on a regular basis. The author's grateful thanks are given to the following persons for providing microbial strains and species. Without their help this work would not be possible. Wolfgang Beyer - University of Hohenheim, Faculty of Agricultural Sciences, Stuttgart, Germany Guido Werner - Robert Koch-Institute, Nosocomial Pathogens and Antibiotic Resistances (FG13), Wernigerode, Germany Alejandra Bosch - CINDEFI, CONICET-CCT La Plata, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina Michal Drevinek - National Institute for Nuclear, Biological and Chemical Protection, Milin, Czech Republic Roland Grunow - Robert Koch-Institute, Highly Pathogenic Microorganisms (ZBS2), Berlin, Germany Daniela Jacob - Robert Koch-Institute, Highly Pathogenic Microorganisms (ZBS2), Berlin, Germany Silke Klee - Robert Koch-Institute, Highly Pathogenic Microorganisms (ZBS2), Berlin, Germany Jörg Rau - Chemisches und Veterinäruntersuchungsamt Stuttgart, Fellbach, Germany Jens Jacob - Robert Koch-Institute, Hospital Hygiene, Infection Prevention and Control (FG14), Berlin, Germany Martin Mielke - Robert Koch-Institute, Department 1 - Infectious Diseases, Berlin, Germany Monika Ehling-Schulz - Functional Microbiology, Institute of Microbiology, University of Veterinary Medicine, Vienna, Austria

License type for data base files (spectra): Creative Commons Attribution Non Commercial 4.0 International (CC-BY-NC): Licensees must credit the original authors by stating their names & the original work's title. Licensees may copy, distribute, display, and perform the work and make derivative works and remixes based on it only for non-commercial purposes.

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Keywords

MALDI TOF Mass Spectrometry, Highly Pathogenic Microorganisms, Spectral Database, Identification

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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