Analysis and Visualization of Spatial Proteomic Data for Tissue Characterization

Author

Fuchsberger, C. ; Hubl, H. ; Schafer, G. ; Pelzer, A. ; Bartsch, G. ; Klocker, H. ; Barbarini, N. ; Bellazzi, R. ; Wieder, W. ; Bonn, G.

Author_Institution

Dept. of Urology, Med. Univ. of Innsbruck, Innsbruck

fYear

2008

fDate

17-19 June 2008

Firstpage

185

Lastpage

190

Abstract

Spatial proteomic profiling of tissue sections provides in situ molecular analysis of proteins and peptides. Analysis and visualization of these high-dimensional data cubes is challenging. We present a methodology for this task based on a novel developed algorithm for the feature identification and reduction step. To show the validity of our approach, we analyzed prostate cancer tissue sections with an adapted kernel-density based clustering algorithm.

Keywords

biological tissues; biology computing; data visualisation; molecular biophysics; pattern clustering; proteins; data analysis; data visualization; feature identification; high-dimensional data cube; in situ molecular analysis; kernel-density based clustering algorithm; peptides; prostate cancer tissue; proteins; spatial proteomic data; spatial proteomic profiling; tissue characterization; Algorithm design and analysis; Biomarkers; Biomedical imaging; Clustering algorithms; Data visualization; Mass spectroscopy; Peptides; Proteins; Proteomics; Smoothing methods; Clustering; Maldi Imaging; Prostate Cancer; Proteomics;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on

Conference_Location

Jyvaskyla

ISSN

1063-7125

Print_ISBN

978-0-7695-3165-6

Type

conf

DOI

10.1109/CBMS.2008.119

Filename

4561984