C. Partl, A. Lex, Marc Streit, Denis Kalkofen, K. Kashofer, D. Schmalstieg,
"enRoute: Dynamic Path Extraction from Biological Pathway Maps for in-Depth Experimental Data Analysis"
, in BioVis'12: Proceedings of the IEEE Symposium on Biological Data Visualization (BioVis'12), Serie Proceedings of IEEE Symposium on Biological Data Visualization, 2012
enRoute: Dynamic Path Extraction from Biological Pathway Maps for in-Depth Experimental Data Analysis
Sprache des Titels:
Proceedings of the IEEE Symposium on Biological Data Visualization (BioVis'12)
Pathway maps are an important source of information when analyzing
functional implications of experimental data on biological processes.
Associating large quantities of data with nodes on a pathway
map and allowing in depth-analysis at the same time, however,
is a challenging task. While a wide variety of approaches for doing
so exist, they either do not scale beyond a few experiments or fail to
represent the pathway appropriately. To remedy this, we introduce
enRoute, a new approach for interactively exploring experimental
data along paths that are dynamically extracted from pathways. By
showing an extracted path side-by-side with experimental data, en-
Route can present large amounts of data for every pathway node.
It can visualize hundreds of samples, dozens of experimental conditions,
and even multiple datasets capturing different aspects of a
node at the same time. Another important property of this approach
is its conceptual compatibility with arbitrary forms of pathways.
Most notably, enRoute works well with pathways that are manually
created, as they are available in large, public pathway databases.
We demonstrate enRoute with pathways from the well-established
KEGG database and expression as well as copy number datasets
from humans and mice with more than 1,000 experiments at the
same time. We validate enRoute in case studies with domain experts,
who used enRoute to explore data for glioblastoma multiforme
in humans and a model of steatohepatitis in mice.
Sprache der Kurzfassung:
Proceedings of IEEE Symposium on Biological Data Visualization