Modeling Genetic Network by Hybrid GP
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{ando:2002:mgnbhg,
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author = "Shin Ando and Hitoshi Iba and Erina Sakamoto",
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title = "Modeling Genetic Network by Hybrid GP",
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booktitle = "Proceedings of the 2002 Congress on Evolutionary
Computation CEC2002",
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editor = "David B. Fogel and Mohamed A. El-Sharkawi and
Xin Yao and Garry Greenwood and Hitoshi Iba and Paul Marrow and
Mark Shackleton",
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pages = "291--296",
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year = "2002",
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publisher = "IEEE Press",
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publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
08855-1331, USA",
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organisation = "IEEE Neural Network Council (NNC), Institution of
Electrical Engineers (IEE), Evolutionary Programming
Society (EPS)",
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ISBN = "0-7803-7278-6",
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month = "12-17 " # may,
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notes = "CEC 2002 - A joint meeting of the IEEE, the
Evolutionary Programming Society, and the IEE. Held in
connection with the World Congress on Computational
Intelligence (WCCI 2002)",
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keywords = "genetic algorithms, genetic programming, artificial
data, differential equations, evolutionary modelling
method, genetic regulatory network modeling, hybrid
algorithm, hybrid genetic programming, least mean
square method, multiple runs, real world data,
regulation, statistical analysis, time series,
differential equations, least mean squares methods,
statistical analysis",
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URL = "http://citeseer.ist.psu.edu/520794.html",
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URL = "http://coblitz.codeen.org:3125/citeseer.ist.psu.edu/cache/papers/cs/17336/http:zSzzSzwww.miv.t.u-tokyo.ac.jpzSz~ibazSztmpzSzando.pdf/modeling-genetic-network-by.pdf",
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DOI = "doi:10.1109/CEC.2002.1006249",
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abstract = "We present an Evolutionary Modelling method for
modeling genetic regulatory networks. The method
features hybrid algorithm of Genetic Programming with
statistical analysis to derive systems of differential
equations. Genetic Programming and Least Mean Square
method were combined to identify a concise form of
regulation between the variables from a given set of
time series. Also, results of multiple runs were
statistically analysed to indicate the term with robust
and significant influence. Our approach was evaluated
in artificial data and real world data.",
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notes = "oai:CiteSeerPSU:520794",
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size = "6 pages",
- }
Genetic Programming entries for
Shin Ando
Hitoshi Iba
Erina Sakamoto
Citations