Difference between revisions of "MicrobeMS - A Matlab Toolbox for Microbial Identification Based on Mass Spectrometry"

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* [[Identification Analysis by Means of LC-MS¹ and ''in silico'' Databases|Identification analysis by means of LC-MS¹ and ''in silico'' databases]]
 
* [[Identification Analysis by Means of LC-MS¹ and ''in silico'' Databases|Identification analysis by means of LC-MS¹ and ''in silico'' databases]]
  
== Identification of MALDI-TOF MS Biomarker Peaks ==
+
== Identification of MS Biomarker Peaks ==
  
 
* Generation of [[Creating Pseudo-Gel Views|pseudo-gel views]] from microbial mass spectra
 
* Generation of [[Creating Pseudo-Gel Views|pseudo-gel views]] from microbial mass spectra

Latest revision as of 18:24, 15 January 2020

Introduction

The software package available from MicrobeMS is a program designed specifically for the analysis of MALDI-TOF mass spectra from microbial samples. The MicrobeMS software was developed by Peter Lasch at the Robert-Koch-Institut (RKI) in Berlin/Germany and can be used to identify microbial strains and species based on their mass spectral patterns. The program is a Matlab-based comprehensive package that operates under Windows 7/8/8.1/10 and LINUX (Debian, MicrobeMS versions later than 0.81). Original MALDI-TOF mass spectra in the format defined by Bruker Daltonics or by Shimadzu (via the mzXML data format) can be imported, processed and converted to a Matlab data matrix format specific to the MicrobeMS program.

The software permits standard mass spectral manipulations such as smoothing, baseline correction, normalization, peak detection, auto-calibration and some other functions. Due to the fact that the software runs also in a complete Windows or LINUX 64-bit environment the number of spectra in the data sets is limited only by the amount of available memory (RAM).

See also the MicrobeMS website for more information.

Getting Started

Preparing Mass Spectra

Description of the Data File Formats

Import and Export of Mass Spectra and Mass Spectral Libraries

Spectral Analysis and Visualization

Identification and Classification

Identification of MS Biomarker Peaks