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Inferring a System of Differential Equations for a Gene Regulatory Network by using Genetic Programming (2001) [19 citations — 3 self]

by Erina Sakamoto ,  Hitoshi Iba
Proc. Congress on Evolutionary Computation
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Abstract:

This paper describes an evolutionary method for identifying the gene regulatory network from the observed time series data of the gene's expression. We use a system of ordinary differential equations as a model of the network and infer their right-hand sides by using Genetic Programming (GP). To explore the search space more effectively in the course of evolution, the least mean square (LMS) method is used along with the ordinary GP. We apply our method to three target networks and empirically show how successfully GP infers the systems of differential equations.

Citations

327 Exploring the metabolic and genetic control of gene expression on a genomic scale, Science 278 – DeRisi, Lyer, et al. - 1997
104 Identification of genetic networks from a small number of gene expression patterns under the Boolean network model. Pac Symp Biocomput – Akutsu, Miyano, et al. - 1999
97 Modeling gene expression with differential equations – Chen, He, et al. - 1999
97 The Theory of Evolution and Dynamical Systems – Hofbauer, Sigmund - 1988
87 Modelling regulatory networks with weight matrices – Weaver, Workman, et al. - 1999
60 Balancing accuracy and parsimony in genetic programming – Zhang, Mühlenbein - 1995
44 Biochemical Systems Analysis. A Study of Function and Design in Molecular Biology – Savageau - 1976
30 Development of a system for the inference of large scale genetic networks – Maki, Tominaga, et al. - 2001
10 Efficient numerical optimization algorithm based on genetic algorithm for inverse problem – Tominaga, Koga, et al.
5 Evolutionary Modeling of Systems of Ordinary Differential Equations with – Cao, Kang, et al. - 2000
5 Identifying Gene Regulatory Network as Differential Equation by Genetic – Sakamoto, Iba - 2000
3 Quantitative Modeling of Gene Regulatory Network -Identifying the Network by Means of Genetic Algorithms – Ando, Iba - 2000
2 Genetic Programming using a Minimum Description Principle – Iba, deGaris, et al. - 1994
1 Inductive Genetic Programming of Polynomial Learning Networks – Nikolaev, Iba - 2000
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