This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A Divide and Conquer Approach for Construction of Large-Scale Signaling Networks from PPI and RNAi Data Using Linear Programming
July-Aug. 2013 (vol. 10 no. 4)
pp. 869-883
Oyku Eren Ozsoy, Inf. Inst., Middle East Tech. Univ., Ankara, Turkey
Tolga Can, Dept. of Comput. Eng., Middle East Tech. Univ., Ankara, Turkey
Inference of topology of signaling networks from perturbation experiments is a challenging problem. Recently, the inference problem has been formulated as a reference network editing problem and it has been shown that finding the minimum number of edit operations on a reference network to comply with perturbation experiments is an NP-complete problem. In this paper, we propose an integer linear optimization (ILP) model for reconstruction of signaling networks from RNAi data and a reference network. The ILP model guarantees the optimal solution; however, is practical only for small signaling networks of size 10-15 genes due to computational complexity. To scale for large signaling networks, we propose a divide and conquer-based heuristic, in which a given reference network is divided into smaller subnetworks that are solved separately and the solutions are merged together to form the solution for the large network. We validate our proposed approach on real and synthetic data sets, and comparison with the state of the art shows that our proposed approach is able to scale better for large networks while attaining similar or better biological accuracy.
Index Terms:
RNA,bioinformatics,computational complexity,genetics,heuristic programming,linear programming,molecular biophysics,optimisation,proteins,biological accuracy,large-scale signaling network construction,PPI data,RNAi data,linear programming,signaling network topology inference,perturbation experiment,inference problem,reference network editing problem,minimum edit operation number,NP-complete problem,integer linear optimization model,ILP model,small signaling network size,gene,computational complexity,large signaling network,heuristic programming,reference network division,reference subnetwork solution merging,Network topology,Proteins,Topology,Linear programming,Data models,Optimization,linear optimization,Signaling network topology,protein-protein interactions,RNA interference
Citation:
Oyku Eren Ozsoy, Tolga Can, "A Divide and Conquer Approach for Construction of Large-Scale Signaling Networks from PPI and RNAi Data Using Linear Programming," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 4, pp. 869-883, July-Aug. 2013, doi:10.1109/TCBB.2013.80
Usage of this product signifies your acceptance of the Terms of Use.