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Mathematical Modeling and Discrete Approximation in Evaluation and Forecasting of Expression-Data

✍ Scribed by J. Gebert; M. Lätsch; S.W. Pickl; G.-W. Weber; R. Wünschiers

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
283 KB
Volume
13
Category
Article
ISSN
1571-0653

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✦ Synopsis

Many problems in computational biology consist in the time-dependent observation of gene expression data. Here, the application of modern methods from dynamical systems, optimization theory, numerical algorithms and the utilization of implicit discrete information lead to a deeper understanding. In [5], we began our research by representing the behavior of gene expression pattern by a system of ordinary differential equations, which we analytically and algorithmically investigated under the parametrical aspect of stability or instability. Our algorithm strongly exploited combinatorial information.

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