Title: "MALDI imaging mass spectrometry: statistical data analysis and current computational challenges"
Speaker: Theodore Alexandrov, Center for Industrial Mathematics (ZeTeM), University of Bremen
Place: HORT 117; October 4, 2011, Tuesday, 4:30pm

Abstract

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) imaging mass spectrometry, also called as MALDI-imaging, is a label-free technology used for spatial molecular analysis of a flat sample. There has been a tremendous development of the MALDI-imaging technology during the last decade. Currently, it is one of the most promising innovative measurement technologies in biochemistry and a powerful and versatile tool for spatial chemical analysis of diverse sample types ranging from biological and plant tissues to bio and polymer thin films. In this talk, we outline computational methods for analyzing MALDI-imaging data with the emphasis on multivariate statistical methods discussing their pros and cons. The methods of unsupervised data-mining as well as supervised classification used for biomarker discovery are elucidated. We also present a high throughput computational pipeline for interpretation of MALDI-imaging data using spatial segmentation. Finally, we discuss current challenges associated with the statistical analysis of MALDI-imaging data.

Associated Reading:
1. J. Watrous, T. Alexandrov, P. Dorrestein (2011) The evolving field of imaging mass spectrometry and its impact on future biological research. Journal of Mass Spectrometry, 46(2):209-222

2. T. Alexandrov, M. Becker, S.-O. Deininger, G. Ernst, L. Wehder, M. Grasmair, F. von Eggeling, H. Thiele, P. Maass (2010) Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering. Journal of Proteome Research, 9(12), 6535-6546



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