New Results
Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in silico Peptide Mass Data
View ORCID ProfilePeter Lasch, Andy Schneider, Christian Blumenscheit, Joerg Doellinger
doi: https://doi.org/10.1101/870089
Peter Lasch
1Robert Koch-Institute, ZBS6 - Proteomics and Spectroscopy, Seestraße 10, Berlin, D-13353, Germany
Andy Schneider
1Robert Koch-Institute, ZBS6 - Proteomics and Spectroscopy, Seestraße 10, Berlin, D-13353, Germany
Christian Blumenscheit
1Robert Koch-Institute, ZBS6 - Proteomics and Spectroscopy, Seestraße 10, Berlin, D-13353, Germany
Joerg Doellinger
1Robert Koch-Institute, ZBS6 - Proteomics and Spectroscopy, Seestraße 10, Berlin, D-13353, Germany

Article usage
Posted December 10, 2019.
Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in silico Peptide Mass Data
Peter Lasch, Andy Schneider, Christian Blumenscheit, Joerg Doellinger
bioRxiv 870089; doi: https://doi.org/10.1101/870089
Subject Area
Subject Areas
- Biochemistry (10739)
- Bioengineering (8019)
- Bioinformatics (27198)
- Biophysics (13941)
- Cancer Biology (11087)
- Cell Biology (15999)
- Clinical Trials (138)
- Developmental Biology (8759)
- Ecology (13247)
- Epidemiology (2067)
- Evolutionary Biology (17322)
- Genetics (11667)
- Genomics (15887)
- Immunology (10996)
- Microbiology (26004)
- Molecular Biology (10609)
- Neuroscience (56370)
- Paleontology (417)
- Pathology (1729)
- Pharmacology and Toxicology (2999)
- Physiology (4530)
- Plant Biology (9593)
- Synthetic Biology (2673)
- Systems Biology (6960)
- Zoology (1508)