Paper Info
Title
Analysis and Visualization of Spatial Proteomic Data for Tissue Characterization
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.
Year
DOI
Venue
2008
10.1109/CBMS.2008.119
CBMS
Keywords
Field
DocType
prostate cancer tissue section,tissue characterization,high-dimensional data cube,feature identification,spatial proteomic data,reduction step,tissue section,clustering algorithm,situ molecular analysis,spatial proteomic,maldi imaging,biomedical imaging,proteomics,molecular biophysics,kernel,data visualization,clustering,feature extraction,high dimensional data,proteins,cancer,biomarkers,data visualisation,mass spectroscopy,data analysis,kernel density,algorithm design and analysis,clustering algorithms
Data mining,Data visualization,Algorithm design,Proteomics,Visualization,Computer science,Feature extraction,MALDI imaging,Proteomic Profiling,Cluster analysis
Conference
ISSN
ISBN
Citations 
2372-9198
978-0-7695-3165-6
0
PageRank 
References 
Authors
0.34
7
10
Name
Order
Citations
PageRank
Christian Fuchsberger1214.19
Heidi Hübl200.34
Georg Schäfer3111.71
Alexandre Pelzer400.34
Georg Bartsch5111.03
Helmut Klocker6111.37
Nicola Barbarini7695.71
Riccardo Bellazzi81313141.89
Wolfgang Wieder900.34
Günther Bonn1000.34