A neural networks algorithm for inferring drug gene regulatory networks from microarray time-series with missing transcription factors information
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- @InProceedings{Floares:2009:IJCNN,
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author = "Alexandru George Floares",
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title = "A neural networks algorithm for inferring drug gene
regulatory networks from microarray time-series with
missing transcription factors information",
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booktitle = "International Joint Conference on Neural Networks,
IJCNN 2009",
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year = "2009",
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month = jun,
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pages = "848--854",
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keywords = "genetic algorithms, genetic programming, algebraic
equations, drug gene regulatory networks, feedback
linearization, mathematical modeling, microarray
time-series, missing transcription factors information,
neural networks algorithm, ordinary differential
equations, reverse engineering algorithm, algebra,
biology computing, data handling, differential
equations, neural nets, reverse engineering, time
series",
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DOI = "doi:10.1109/IJCNN.2009.5179081",
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ISSN = "1098-7576",
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abstract = "Mathematical modeling gene regulatory networks is
important for understanding and controlling them, with
various drugs and their dosage. The ordinary
differential equations approach is sensible but also
very difficult. Our reverse engineering algorithm
(RODES), based on neural networks feedback
linearization and genetic programming, takes as inputs
high-throughput (e.g., microarray) time series data and
automatically infer an accurate ordinary differential
equations model. The algorithm decouples the systems of
differential equations, reducing the problem to that of
revere engineering individual algebraic equations, and
is able to deal with missing information,
reconstructing the temporal series of the transcription
factors or drug related compounds which are usually
missing in microarray experiments. It is also able to
incorporate 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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notes = "Also known as \cite{5179081}",
- }
Genetic Programming entries for
Alexandru Floares
Citations