Automatic Inferring Drug Gene Regulatory Networks with Missing Information Using Neural Networks and Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Floares:2008:ijcnn,
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author = "Alexandru George Floares",
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title = "Automatic Inferring Drug Gene Regulatory Networks with
Missing Information Using Neural Networks and Genetic
Programming",
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booktitle = "2008 IEEE World Congress on Computational
Intelligence",
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year = "2008",
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editor = "Jun Wang",
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pages = "3078--3085",
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address = "Hong Kong",
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month = "1-6 " # jun,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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isbn13 = "978-1-4244-1821-3",
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file = "NN0852.pdf",
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DOI = "doi:10.1109/IJCNN.2008.4634233",
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ISSN = "1098-7576",
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abstract = "Automatically inferring drug gene regulatory networks
models from microarray time series data is a
challenging task. The ordinary differential equations
models are sensible, but difficult to build. We
extended our reverse engineering algorithm for gene
networks (RODES), based on genetic programming, by
adding a neural networks feedback linearisation
component. Thus, RODES automatically discovers the
structure, estimate the parameter, and identify the
molecular mechanisms, even when information is missing
from the data. It produces systems of ordinary
differential equations from experimental or simulated
microarray time series data. On simulated data the
accuracy and the CPU time were very good. This is due
to reducing the reversing of an ordinary differential
equations system to that of individual algebraic
equations, and to the possibility of incorporating
common a priori knowledge. To our knowledge, this is
the first realistic reverse engineering algorithm,
based on genetic programming and neural networks,
applicable to large gene networks.",
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keywords = "genetic algorithms, genetic programming",
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notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
EPS and the IET. Also known as \cite{4634233}",
- }
Genetic Programming entries for
Alexandru Floares
Citations