mineXpert2 is part of the msXpertSuite software package.

mineXpert2 is a full rewrite of the first mineXpert software published in 2019 in ACS Journal of Proteome Research.

mineXpert2 has been published (2021) in the Journal of the American Society for Mass Spectrometry.


  • 2022 06 17 Version 8.3.0
    - New release improving the navigation in the plots, specifically when the X/Y axes are locked and when the mouse wheel is used to zoom/unzoom (thanks to Kevin Hooijschuur for the reports).
  • 2022 02 28 Version 8.2.0
    - New release featuring a new noise reduction processing for mass spectral traces (see the related documentation bits here). Consider this experimental, as there are still rough edges.
  • 2021 04 27 Version 8.1.1
    - New release featuring a new noise reduction processing for color maps (see the related documentation bits here).
  • 2021 03 24 Version 8.0.1
    - Big new release with important new feature: the skewed selection polygon-based integrations that allow selecting color map regions matching the "sloped bands" features often visible in mz = f(dt) color maps (see the related documentation bits here).
  • 2021 01 05 Version 7.4.0
    - Added feature to limit the number of processors that mineXpert2 might use during the integration computations;
    - Added a shortcut to the MS level setting to each composite plot widget. That makes it more evident how to select the MS level for the next integration computation.
    - A new software delivery format is now available, the AppImage format that is very convenient: it is a simple file that in fact contains an internal file system that ships all the required libraries. This makes the AppImage format particularly appealing when the software needs to run on a variety of GNU/Linux platforms. The AppImage-based mineXpert2 software package has been tested on Fedora-22 and on CentOS-8.3.2011.
    - The binary packages are now shipped from a new repository. Head on to the Downloads page!
  • 2020 10 23 Version 7.3.0
    - Added feature to compute the intensities (colored scale) of color maps (heat maps) as log10 of the initial value, thus allowing the visualization of less abundant species.
    - Updated all the menus so that a keyboard sequence shortcut is available to call them with a proper mnemonic.
    - Updated the user manual.
  • 2020 10 12 Version 7.1.0
    - Fixed bug with failed integration to a mass spectrum starting from a XIC chromatogram that was computed using the specialized dialog window.
  • 2020 10 02 Version 7.0.1
    - Add new modalities for incorporating new computation results into preexisting traces: new results might be combined into existing traces either by addition or subtraction. The latter modality is useful to remove noise signal.
    - Deep improvements with the mass spectrometric MS^n data.
    - Improved the way filtering criteria are entered (ranges, tolerance) in the mass spectral data set table view.
    - Updates to the user manual to document the new features.
  • 2020 07 24 Version 6.0.2
    - Fix: the program still accessed the user manual from the previous version.

This is a comparison of the software versions:

  • mineXpert2 is now coded with true execution parallelism, delivering much better calculation performance and user experience (no window lock-ups when intensive tasks are performed);
  • mineXpert2 is MSn-capable, while mineXpert was MS1-only;
  • mineXpert2 now features more mass spectral integration types, like color map views not available in mineXpert;
  • mineXpert2 has a very much improved data window management with lots of new features that aid in the mass spectrometric data comparisons across samples.

If you use this program, please cite it using this reference:

Filippo Rusconi (2019) mineXpert: Biological Mass Spectrometry Data Visualization and Mining with Full JavaScript Ability. Journal of Proteome Research, 18 (5), 2254-2259. DOI: 10.1021/acs.jproteome.9b00099

Video screen captures showcasing mineXpert2 features here.

To download the software, please check the Downloads menu on the side bar.

mineXpert2 has the following major features:

  • Load any number of mass data files, either fully in memory or in streamed mode (when the files are larger than the available RAM);
  • A typical data mining session would involve the following steps/actions:
    - Open a mass spectrometry file and immediately compute a TIC chromatogram, show that chromatogram in a dedicated window. If the data are from an ion mobility mass spectrometry (IM-MS) experiment, compute a mz=f(dt) color map. The TIC chromatogram and the color map are then the starting points for the mining of the data.
    - Perform a wide variety of integrations to a mass spectrum or a drift spectrum. Each new spectrum is displayed in its dedicated window (the TIC chromatogram window, the Color map window, the Mass spectrum window and the Drift spectrum window). Each new plot (be it a TIC chromatogram, a mass spectrum, a drift spectrum or any kind of color map) can be the starting point of another integration to either the same kind of data view or to any other kind of data view. Various integrations in sequence allow the user to elaborate data mining processes that drill each time farther in the depth of the data.
  • Each plot has specific functions associated to it: export as a (x,y) file, automatic recording of the relevant data of signalled peaks into a file using a specific easy-to-understand grammar.
  • A tabulated view of the whole set of mass spectra in a given file allows one to filter the data according to a number of parameters (retention time, ion mobility, MS level, precursor ion m/z value, precursor ion charge, for example). Once the initial data set has been reduced to the desired mass spectra, the user may select them and use them to compute tailored mass spectral data integrations.
  • Extremely flexible|powerful data views are available to allow sophisticated mass spectral data comparisons either from the same data set or from multiple data sets.
  • The IsoSpec module allows one to perform isotopic cluster calculations and to shape the obtained centroid values into Gaussian shapes that create the whole mass spectrum encompassing the various peaks of the isotopic cluster. The obtained mass spectrum can then be plotted in a plot widget like any other mass spectrum, which allows fine comparisons between experimental data and simulated data.