An algorithm to analyze stability of gene-expression patterns

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


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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: