SCiLS Lab by Bruker Daltonics

Manufacturer Bruker Daltonics
The advanced mass spectrometry imaging software solution

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SCiLS Lab is a leading software for analysis of mass spectrometry imaging data and is an integral part of Bruker’s MALDI molecular imager solution. Comparative analysis of multiple samples can be visualized in both 2D and 3D allowing a multitude of applications in pharmaceutical, medical, and industrial research.

Statistical analysis of MALDI imaging data has never been easier with the software from SCiLS GmbH. The product family SCiLS Lab supports all major Bruker instruments and is part of the integrated solutions Molecular Drug Imager and the rapifleX MALDI Tissue typer.


The software package for Bruker mass spectrometers, SCiLS Lab can be used for the analysis of one or more MALDI imaging datasets. Multiple data sets can be loaded and spatially aligned in a tiled manner. Compositions of data sets of virtually unlimited size can be visualized and statistically analyzed for detailed interpretation. Also, SCiLS Lab can be used for construction of 3D MALDI imaging data from consecutive 2D datasets, and visualization and analysis of 3D MALDI imaging data.


The software package for vendor-neutral data analysis, SCiLS Lab MVS can be used for the analysis of mass spectrometry imaging datasets based on the open imzML data format. SCiLS Lab MVS offers all features of SCiLS Lab for non-Bruker mass spectrometers and it allows the statistical analysis and visualization of mass spectrometry imaging data of virtually unlimited size in two and three spatial dimensions.

SCiLS Cloud

The set of tools for distributed workflows, all combined in one easy web solution, SCiLS Cloud meets the rising challenge in clinical research studies: Different scientific disciplines, many teams and partners located across the world need to work closely together – without barriers, in a secure and easy environment for efficient collaboration.

Key Features

  • Instant visualization of ion images spectra
  • Multiple annotations for characterizing regions in clinical and preclinical studies
  • Process data sets of virtually unlimited size
  • Comparative analysis for uncovering discriminative m/z-markers
  • Co-localization analysis for discovering of correlated m/z-values
  • Spatial segmentation for automatic annotation of prominent features
  • Extraction of underlying trends
  • Mixture decomposition
  • Classification model calculation based on training data and classification of new samples

To access the SCiLS Cloud web-based service, go to and browse data shared within the scientific community. For more information about the SCiLS Lab product line, such as features, software downloads, and demo data visit SCiLS directly.