By Topic

On Data and Visualization Models for Signaling Pathways

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ratprasartporn, N. ; Dept. of Electr. Eng. & Comput. Sci., Case Western Reserve Univ., Cleveland, OH ; Cakmak, A. ; Ozsoyoglu, G.

Signaling pathways are chains of interacting proteins, through which the cell converts a (usually) extracellular signal into a biological response. The number of known signaling pathways in the biological literature and on the Web has been increasing at a very high rate, thus demanding a need for efficient ways of storing, visualizing, querying, and mining signaling pathways. In this paper, first we briefly compare the data modeling and visualization capabilities of existing signaling pathways systems. Then, we present a signaling pathway data model and its visualization that subsumes the existing models. Our model visualizes a signaling pathway (a) as a nested graph, (b) with explicit location information (e.g., cell, tissue, organelle, nucleus, etc.), and (c) in four abstraction levels, namely, the levels of molecule-to-molecule signaling steps, collapsed sub-pathways, molecule-to-pathway connections, and pathway-to-pathway connections. We model (1) the effects of specific signaling steps, (2) state changes of signaling molecules, (3) various (extensible) structural/physical changes of signaling molecules such as complex formation, dissociation, assembly, oligomerization, di-/trimerization, cleavage and degradation, (4) condensation/hydrolysis signaling steps, and (5) exchanges and translocations as signaling steps. The visualization model gracefully models incomplete information and hierarchical levels of signaling molecules. Finally, we introduce a completely new visualization dimension for pathways, namely, gene ontology (GO)-based functional visualizations of pathways. We believe that functional visualizations of pathways provides new opportunities in understanding, defining and comparing existing pathways, and in helping discover new ones

Published in:

Scientific and Statistical Database Management, 2006. 18th International Conference on

Date of Conference:

0-0 0