- author = "Erina Sakamoto and Hitoshi Iba",
- title = "Inferring a System of Differential Equations for a Gene Regulatory Network by using Genetic Programming",
- booktitle = "Proceedings of the 2001 Congress on Evolutionary Computation CEC2001",
- year = "2001",
- pages = "720--726",
- address = "COEX, World Trade Center, 159 Samseong-dong, Gangnam-gu, Seoul, Korea",
- publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
- month = "27-30 " # may,
- organisation = "IEEE Neural Network Council (NNC), Evolutionary Programming Society (EPS), Institution of Electrical Engineers (IEE)",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, least mean squares",
- ISBN = "0-7803-6658-1",
-
URL = "
http://www.miv.t.u-tokyo.ac.jp/ibalab/papers/2001/cec2001-es.pdf",
-
URL = "
http://citeseer.ist.psu.edu/484086.html",
-
DOI = "
doi:10.1109/CEC.2001.934462",
- 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.",
-
notes = "CEC-2001 - A joint meeting of the IEEE, Evolutionary
Programming Society, Galesia, and the IEE.
IEEE Catalog Number = 01TH8546C,
Library of Congress Number =",
