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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE Symposium on Computer-Based Medical Systems |
| Pages | 185-190 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | 21st IEEE International Symposium on Computer-Based Medical Systems, CBMS 2008 - Jyvaskyla, Finland Duration: Jun 17 2008 → Jun 19 2008 |
Other
| Other | 21st IEEE International Symposium on Computer-Based Medical Systems, CBMS 2008 |
|---|---|
| Country | Finland |
| City | Jyvaskyla |
| Period | 6/17/08 → 6/19/08 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Analysis and visualization of spatial proteomic data for tissue characterization. / Fuchsberger, C.; Hübl, H.; Schäfer, G.; Pelzer, A.; Bartsch, G.; Klocker, H.; Barbarini, N.; Bellazzi, R.; Wieder, W.; Bonn, G.
Proceedings - IEEE Symposium on Computer-Based Medical Systems. 2008. p. 185-190 4561984.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Analysis and visualization of spatial proteomic data for tissue characterization
AU - Fuchsberger, C.
AU - Hübl, H.
AU - Schäfer, G.
AU - Pelzer, A.
AU - Bartsch, G.
AU - Klocker, H.
AU - Barbarini, N.
AU - Bellazzi, R.
AU - Wieder, W.
AU - Bonn, G.
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=51849152033&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51849152033&partnerID=8YFLogxK
U2 - 10.1109/CBMS.2008.119
DO - 10.1109/CBMS.2008.119
M3 - Conference contribution
AN - SCOPUS:51849152033
SN - 9780769531656
SP - 185
EP - 190
BT - Proceedings - IEEE Symposium on Computer-Based Medical Systems
ER -