Considering Unknown Unknowns: Reconstruction of Nonconfoundable Causal Relations in Biological Networks

Sadeh, Mohammad J. and Moffa, Giusi and Spang, Rainer. (2013) Considering Unknown Unknowns: Reconstruction of Nonconfoundable Causal Relations in Biological Networks. Journal of Computational Biology, 20 (11). pp. 920-932.

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Official URL: https://edoc.unibas.ch/81038/

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Our current understanding of cellular networks is rather incomplete. We over look important but so far unknown genes and mechanisms in the pathways. Moreover, we often only have a partial account of the molecular interactions and modifications of the known players. When analyzing the cell, we look through narrow windows leaving potentially important events in blind spots. Network reconstruction is naturally confined to what we have observed. Little is known on how the incompleteness of our observations confounds our interpretation of the available data. Here we ask which features of a network can be confounded by incomplete observations and which cannot. In the context of nested effects models, we show that in the presence of missing observations or hidden factors a reliable reconstruction of the full network is not feasible. Nevertheless, we can show that certain characteristics of signaling networks like the existence of cross-talk between certain branches of the network can be inferred in a nonconfoundable way. We derive a test for inferring such nonconfoundable characteristics of signaling networks. Next, we introduce a new data structure to represent partially reconstructed signaling networks. Finally, we evaluate our method both on simulated data and in the context of a study on early stem cell differentiation in mice.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Mathematik > Statistik (Moffa)
UniBasel Contributors:Moffa, Giusi
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Mary Ann Liebert
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:13 Apr 2021 14:14
Deposited On:13 Apr 2021 14:14

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