Biology – Quantitative Biology – Molecular Networks
Scientific paper
2010-12-26
Journal of Theoretical Biology 279 (2011) 29-43
Biology
Quantitative Biology
Molecular Networks
33 pages, 6 figures
Scientific paper
10.1016/j.jtbi.2011.03.020
In a previous paper we introduced a method called augmented sparse reconstruction (ASR) that identifies links among nodes of ordinary differential equation networks, given a small set of observed trajectories with various initial conditions. The main purpose of that technique was to reconstruct intracellular protein signaling networks. In this paper we show that a recursive augmented sparse reconstruction generates artificial networks that are homologous to a large, reference network, in the sense that kinase inhibition of several reactions in the network alters the trajectories of a sizable number of proteins in comparable ways for reference and reconstructed networks. We show this result using a large in-silico model of the epidermal growth factor receptor (EGF-R) driven signaling cascade to generate the data used in the reconstruction algorithm. The most significant consequence of this observed homology is that a nearly optimal combinatorial dosage of kinase inhibitors can be inferred, for many nodes, from the reconstructed network, a result potentially useful for a variety of applications in personalized medicine.
Liotta Lance
Napoletani Domenico
Petricoin Emanuel
Sauer Timothy
Signore Michele
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