Reconstructing Boolean Models of Signaling

TitleReconstructing Boolean Models of Signaling
Publication TypeConference Paper
Year of Publication2012
AuthorsSharan, R., & Karp R. M.
Page(s)261-271
Other Numbers3291
Abstract

Since the first emergence of protein-protein interaction networks, more than a decade ago, they have been viewed as static scaffolds of the signaling-regulatory events taking place in the cell and their analysis has been mainly confined to topological aspects. Recently, functional models of these networks have been suggested, ranging from Boolean to constraint-based ones. However, learning such models from large-scale data remains a formidable task and most modeling approaches rely on extensive human curation. Here we provide a generic approach to learning Boolean models automatically from data. We apply our approach to growth and inflammatory signaling systems in human and show how the learning phase can improve the fit of the model to experimental data, remove spurious interactions and lead to better understanding of the system at hand.

Bibliographic Notes

Proceedings of the 16th Annual International Conference on Research in Computational Molecular Biology (RECOMB 2012), Barcelona, Spain, pp. 261-271

Abbreviated Authors

R. Sharan and R. M. Karp

ICSI Research Group

Algorithms

ICSI Publication Type

Article in conference proceedings