NDLI: Multivariate Analysis of Imaging Mass Spectrometry Data

Content Provider	IEEE Xplore Digital Library
Author	Muir, E.R. Ndiour, I.J. Le Goasduff, N.A. Moffitt, R.A. Liu, Y. Sullards, M.C. Merrill, A.H. Chen, Y. Wang, M.D.
Copyright Year	2007
Description	Author affiliation: Emory Univ., Atlanta (Muir, E.R.; Moffitt, R.A.; Wang, M.D.)
Abstract	Imaging mass spectrometry can be used to reveal spatial distributions of multiple molecular species in a 2D biological sample. Due to the large amount of data produced by this technology, it is difficult and time-consuming to manually extract meaningful results from imaging mass spectrometry experimentation. We have developed and implemented an original approach to easily and consistently process mass spectrometry imaging data with the goal of automatically identifying interesting regions of molecule expression. Based on multivariate analysis techniques such as principal component analysis, the system allows researchers to conveniently define and visualize spatial regions based on spectral similarity. Features of our system are demonstrated on mouse cerebellum data.
Starting Page	472
Ending Page	479
File Size	2721777
Page Count	8
File Format	PDF
ISBN	9781424415090
DOI	10.1109/BIBE.2007.4375603
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image analysis Mass spectroscopy Principal component analysis Data visualization Quality control Mice Data processing Biochemical analysis Linear discriminant analysis Biology computing multivariate analysis imaging mass spectrometry
Content Type	Text
Resource Type	Article

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