The analysis of time-series gene expression data, which are obtained from DNA-microarray chip experiments, is a challenging problem that has significant applications in the areas of life and environmental sciences, computational biology, and engineering sciences. The goal is to understand the interactions of a set of genes among each others, based on experimental data and the data coming from environmental measurements.
We analyze time-discrete target-environment regulatory systems, especially for gene-environment networks in which the target variables represent the expression levels of the genes and external factors (e.g., transcription factors, toxins or radiation). We introduce a formulation as a mixed-integer nonlinear programming (MINLP) problem. We compare different schemes of timediscretization in our computational experiments.
- Çankaya University, Ankara, Turkey
- Middle Eastern Technical Univ., Ankara, Turkey
- Liana Amaya Moreno, Özlem Defterli, Armin Fügenschuh, Gerhard-Wilhelm Weber, Vester's Sensitivity Model for Genetic Networks with Time-Discrete Dynamics, Technical Report, Applied Mathematics and Optimization Series AMOS#1, 2014.
- Özlem Defterli, Armin Fügenschuh, Gerhard-Wilhelm Weber, Modern Tools for the Time-Discrete Dynamics and Optimization of Gene-Environment Networks, Communications in Nonlinear Science and Numerical Simulation, Vol. 16, No. 12, pp. 4768 – 4779, 2011.
- Özlem Defterli, Armin Fügenschuh, Gerhard-Wilhelm Weber, Modern Tools for the Time-Discrete Dynamics and Optimization of Gene-Environment Networks , 3rd Conference on Nonlinear Science and Complexity (NSC10), 2010.
- Özlem Defterli, Armin Fügenschuh, Gerhard-Wilhelm Weber, New Discretization and Optimization Techniques with Results in the Dynamics of Gene-Environment Networks , 3rd Global Conference on Power Control and Optimization (PCO 2010), 2010.