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MSI has emerged as a technique suited to resolving metabolism within complex cellular systems; where understanding the spatial variation of metabolism is vital for making a transformative impact on science. Unfortunately, the scale of MSI data and complexity of analysis presents an insurmountable barrier to scientists where a single 2D-image may be many gigabytes and comparison of multiple images is beyond the capabilities available to most scientists. The OpenMSI project will overcome these challenges, allowing broad use of MSI to researchers by providing a web-based gateway for management and storage of MSI data, the visualization of the hyper-dimensional contents of the data, and the statistical analysis.
Assists users to analyze mass spectrometry imaging data. SCILS Lab includes a lot of functionalities allowing researchers to display multiple samples in both 2D and 3D and permitting a multitude of applications in pharmaceutical, medical, and industrial research. This software is composed of several features among which comparative analysis for uncovering discriminative m/z-markers, classification model calculation based on training data and classification of new samples, or extraction of underlying trends.

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