Image data normalization software tools | Mass spectrometry imaging analysis
Normalization is critically important for the proper interpretation of matrix-assisted laser desorption/ionization (MALDI) imaging datasets. The effects of the commonly used normalization techniques based on total ion count (TIC) or vector norm normalization are significant, and they are frequently beneficial.
A vendor-neutral interface built on the Matlab platform designed to view and perform data analysis of Mass Spectrometry Imaging (MSI) data. A standalone version of MSiReader for which Matlab is not required is also provided. People who are unfamiliar with the Matlab language will have little difficulty navigating the user friendly interface, and users with Matlab programming experience can adapt and customize MSiReader for their own needs.
Provides quantitation of target compounds (taking into account biological matrix effect) following Mass spectrometry imaging experiments. Quantinetix is a Quantitative Imaging Mass Spectrometry Software which offers normalization to get “real images” and provides concentration of target compounds. It is specially designed to ADMET study, PK/PD study, Toxicity study, In support of Whole Body Autoradiography and Proteomics and Lipidomics studies.
Presents an improved data analysis pipeline based on a new peak picking method for exploring imaging mass spectrometry data. EXIMS consists of five consecutive main steps: where the first step involves spectra preprocessing. Then, Sliding Window Normalization (SWN) is used to normalize the spectra and limit the influence of high intensity peaks. Third, image de-noising and contrast enhancement are used to improve the visualization of intensity images. Fourth, peak picking is performed by processing the individual intensity images. Finally, intensity images are clustered using the fuzzy cmeans clustering algorithm.
A mass spectrometry imaging toolbox for statistical analysis. Cardinal is an R package that implements statistical and computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.
Enables the visualization, analysis of large data sets. msIQuant allows users to display and study data sets without data reduction. It has a quantitation function that generates calibration standard curves from series of standards that can be used to determine the concentrations of specific analyses. In summary, it supplies solution for accessing and evaluating data sets, quantifying drugs and endogenous compounds in tissue areas of interest, and for processing mass spectra and images.
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