Title
PANI: an interactive data-driven tool for target prioritization in signaling networks
Abstract
Biological network analysis often aims at the target identification problem, which is to predict which molecule to inhibit (or activate) for a disease treatment to achieve optimum efficacy and safety. A related goal, arising from the increasing availability of high-throughput screening (HTS), is to suggest many molecules as potential targets. The target prioritization problem is to predict a subset of molecules in a given disease-associated network which is likely to include successful drug targets. Sensitivity analysis prioritizes targets in a dynamic network model according to principled criteria, but fails to penalize off-target effects, and does not scale for large networks. In this demonstration, we present PANI(Putative TArget Nodes PrIoritization), a novel interactive system that addresses these limitations. It prunes and ranks the possible target nodes by exploiting concentration-time profiles and network structure (topological) information and visually display them in the context of the signaling network. Through the interactive user interface, we demonstrate various innovative features of PANI that enhance users' understanding of the prioritized nodes.
Year
DOI
Venue
2012
10.1145/2110363.2110471
IHI
Keywords
Field
DocType
network structure,target identification problem,dynamic network model,disease-associated network,possible target node,successful drug target,sensitivity analysis prioritizes target,target prioritization,biological network analysis,interactive data-driven tool,potential target,large network,high throughput screening,biological network,sensitivity analysis,drug targeting
Dynamic network analysis,Data mining,Large networks,Data-driven,Computer science,Biological network,Prioritization,User interface,Parameter identification problem,Distributed computing,Network structure
Conference
Citations 
PageRank 
References 
0
0.34
7
Authors
6
Name
Order
Citations
PageRank
Huey-Eng Chua1236.55
Sourav S. Bhowmick21519272.35
Lisa Tucker-Kellogg3237.38
Yingqi Wang400.34
C. Forbes Dewey, Jr.5122.60
Hanry Yu6294.16