An algorithm to analyze stability of gene-expression patterns

Date

2006-05-01

Author

Gebert, J
Latsch, M
Pickl, SW
Weber, Gerhard Wilhelm
Wunschiers, R

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

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Many problems in the field of computational biology consist of the analysis of so-called gene-expression data. The successful application of approximation and optimization techniques, dynamical systems, algorithms and the utilization of the underlying combinatorial structures lead to a better understanding in that field. For the concrete example of gene-expression data we extend an algorithm, which exploits discrete information. This is lying in extremal points of polyhedra, which grow step by step, up to a possible stopping. We study gene-expression data in time, mathematically model it by a time-continuous system, and time-discretize this system. By our algorithm we compute the regions of stability and instability. We give a motivating introduction from genetics, present biological and mathematical interpretations of (in)stability, point out structural frontiers and give an outlook to future research.

Subject Keywords

Applied Mathematics, Discrete Mathematics and Combinatorics

URI

https://hdl.handle.net/11511/56601

Journal

DISCRETE APPLIED MATHEMATICS

DOI

https://doi.org/10.1016/j.dam.2004.08.011

Collections

Graduate School of Applied Mathematics, Article

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Citation Formats

J. Gebert, M. Latsch, S. Pickl, G. W. Weber, and R. Wunschiers, “An algorithm to analyze stability of gene-expression patterns,” DISCRETE APPLIED MATHEMATICS, pp. 1140–1156, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56601.