Identifying latent dynamic components in biological systems

Kondofersky I, Fuchs C, Theis FJ (2015)
IET Systems Biology 9(5): 193-203.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Kondofersky, Ivan; Fuchs, ChristianeUniBi ; Theis, Fabian J.
Abstract / Bemerkung
In computational systems biology, the general aim is to derive regulatory models from multivariate readouts, thereby generating predictions for novel experiments. In the past, many such models have been formulated for different biological applications. The authors consider the scenario where a given model fails to predict a set of observations with acceptable accuracy and ask the question whether this is because of the model lacking important external regulations. Real-world examples for such entities range from microRNAs to metabolic fluxes. To improve the prediction, they propose an algorithm to systematically extend the network by an additional latent dynamic variable which has an exogenous effect on the considered network. This variable's time course and influence on the other species is estimated in a two-step procedure involving spline approximation, maximum-likelihood estimation and model selection. Simulation studies show that such a hidden influence can successfully be inferred. The method is also applied to a signalling pathway model where they analyse real data and obtain promising results. Furthermore, the technique can be employed to detect incomplete network structures.
Erscheinungsjahr
2015
Zeitschriftentitel
IET Systems Biology
Band
9
Ausgabe
5
Seite(n)
193-203
ISSN
1751-8849
eISSN
1751-8857
Page URI
https://pub.uni-bielefeld.de/record/2934025

Zitieren

Kondofersky I, Fuchs C, Theis FJ. Identifying latent dynamic components in biological systems. IET Systems Biology. 2015;9(5):193-203.
Kondofersky, I., Fuchs, C., & Theis, F. J. (2015). Identifying latent dynamic components in biological systems. IET Systems Biology, 9(5), 193-203. doi:10.1049/iet-syb.2014.0013
Kondofersky, I., Fuchs, C., and Theis, F. J. (2015). Identifying latent dynamic components in biological systems. IET Systems Biology 9, 193-203.
Kondofersky, I., Fuchs, C., & Theis, F.J., 2015. Identifying latent dynamic components in biological systems. IET Systems Biology, 9(5), p 193-203.
I. Kondofersky, C. Fuchs, and F.J. Theis, “Identifying latent dynamic components in biological systems”, IET Systems Biology, vol. 9, 2015, pp. 193-203.
Kondofersky, I., Fuchs, C., Theis, F.J.: Identifying latent dynamic components in biological systems. IET Systems Biology. 9, 193-203 (2015).
Kondofersky, Ivan, Fuchs, Christiane, and Theis, Fabian J. “Identifying latent dynamic components in biological systems”. IET Systems Biology 9.5 (2015): 193-203.

2 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Systems Pharmacology in Small Molecular Drug Discovery.
Zhou W, Wang Y, Lu A, Zhang G., Int J Mol Sci 17(2), 2016
PMID: 26901192
Inferring catalysis in biological systems.
Kondofersky I, Theis FJ, Fuchs C., IET Syst Biol 10(6), 2016
PMID: 27879475

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