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Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn

Ed. by Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Editorial Board: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan

4 Issues per year


CiteScore 2016: 0.93

SCImago Journal Rank (SJR) 2016: 0.416

Open Access
Online
ISSN
1613-4516
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Volume 9, Issue 1

Issues

On the Importance of Mathematical Methods for Analysis of MALDI-Imaging Mass Spectrometry Data

Dennis Trede
  • Corresponding author
  • Steinbeis Innovation Center SCiLS (Scientific Computing in Life Sciences), Richard-Dehmel-Str. 69, 28211 Bremen, http://www.scils.de Germany
  • Zentrum für Technomathematik, Universität Bremen, Bibliothekstr. 1, 28359 Bremen, http://www.zetem.uni-bremen.de, Germany
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jan Hendrik Kobarg
  • Zentrum für Technomathematik, Universität Bremen, Bibliothekstr. 1, 28359 Bremen, http://www.zetem.uni-bremen.de, Germany
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/ Janina Oetjen
  • Zentrum für Technomathematik, Universität Bremen, Bibliothekstr. 1, 28359 Bremen, http://www.zetem.uni-bremen.de Germany
  • MALDI Imaging Lab, Universität Bremen, Leobener Str., 28359 Bremen, http://www.maldi.uni-bremen.de, Germany
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/ Herbert Thiele / Peter Maass
  • Steinbeis Innovation Center SCiLS (Scientific Computing in Life Sciences), Richard-Dehmel-Str. 69, 28211 Bremen, http://www.scils.de Germany
  • Zentrum für Technomathematik, Universität Bremen, Bibliothekstr. 1, 28359 Bremen, http://www.zetem.uni-bremen.de, Germany
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  • De Gruyter OnlineGoogle Scholar
/ Theodore Alexandrov
  • Steinbeis Innovation Center SCiLS (Scientific Computing in Life Sciences), Richard-Dehmel-Str. 69, 28211 Bremen, http://www.scils.de United States of America
  • Zentrum für Technomathematik, Universität Bremen, Bibliothekstr. 1, 28359 Bremen, http://www.zetem.uni-bremen.de United States of America
  • MALDI Imaging Lab, Universität Bremen, Leobener Str., 28359 Bremen, http://www.maldi.uni-bremen.de United States of America
  • Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, 9500 Gilman Drive, MC 0657, La Jolla, Ca 92093-0657, http://pharmacy.ucsd.edu, United States of America
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Published Online: 2016-10-18 | DOI: https://doi.org/10.1515/jib-2012-189

Summary

In the last decade, matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS), also called as MALDI-imaging, has proven its potential in proteomics and was successfully applied to various types of biomedical problems, in particular to histopathological label-free analysis of tissue sections. In histopathology, MALDI-imaging is used as a general analytic tool revealing the functional proteomic structure of tissue sections, and as a discovery tool for detecting new biomarkers discriminating a region annotated by an experienced histologist, in particular, for cancer studies.

A typical MALDI-imaging data set contains 108 to 109 intensity values occupying more than 1 GB. Analysis and interpretation of such huge amount of data is a mathematically, statistically and computationally challenging problem. In this paper we overview some computational methods for analysis of MALDI-imaging data sets. We discuss the importance of data preprocessing, which typically includes normalization, baseline removal and peak picking, and hightlight the importance of image denoising when visualizing IMS data.

About the article

Published Online: 2016-10-18

Published in Print: 2012-03-01


Citation Information: Journal of Integrative Bioinformatics, Volume 9, Issue 1, Pages 1–11, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2012-189.

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© 2012 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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