Vester's Sensitivity Model for Genetic Networks with Time-Discrete Dynamics

Date

2014-07-03

Author

Moreno, Liana Amaya
DEFTERLİ, ÖZLEM
Fuegenschuh, Armin
Weber, Gerhard Wilhelm

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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We propose a new method to explore the characteristics of genetic networks whose dynamics are described by a linear discrete dynamical model x(t+1) = Ax(t). The gene expression data x(t) is given for various time points and the matrix A of interactions among the genes is unknown. First we formulate and solve a parameter estimation problem by linear programming in order to obtain the entries of the matrix A. We then use ideas from Vester's Sensitivity Model, more precisely, the Impact Matrix, and the determination of the Systemic Roles, to understand the interactions among the genes and their role in the system. The method identifies prominent outliers, that is, the most active, reactive, buffering and critical genes in the network. Numerical examples for different datasets containing mRNA transcript levels during the cell cycle of budding yeast are presented.

Subject Keywords

Linear programming, Parameter estimation, Discrete Dynamical System

URI

https://hdl.handle.net/11511/53485

Conference Name

1st International Conference on Algorithms for Computational Biology (AlCoB)

Collections

Graduate School of Applied Mathematics, Conference / Seminar

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Citation Formats

L. A. Moreno, Ö. DEFTERLİ, A. Fuegenschuh, and G. W. Weber, “Vester’s Sensitivity Model for Genetic Networks with Time-Discrete Dynamics,” Tarragona, Spain, 2014, vol. 8542, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53485.