A Methodology for Disease Gene Association using Centrality Measures
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- @InProceedings{Heravi:2016:CEC,
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author = "Ashkan Entezari Heravi and Sheridan Houghten",
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title = "A Methodology for Disease Gene Association using
Centrality Measures",
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booktitle = "Proceedings of 2016 IEEE Congress on Evolutionary
Computation (CEC 2016)",
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year = "2016",
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editor = "Yew-Soon Ong",
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pages = "24--31",
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address = "Vancouver",
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month = "24-29 " # jul,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-5090-0623-6",
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DOI = "doi:10.1109/CEC.2016.7743774",
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abstract = "Disease-gene association attempts to determine which
genes are involved with genetic diseases. Various
methodologies have been applied to this problem for
different diseases. In earlier work, two evolutionary
approaches were used to analyse the complex network of
gene interaction. This paper presents an improvement
upon the genetic programming approach using a variety
of centrality measures to analyze the networks. This
approach is applied to both Parkinson's disease and
breast cancer.",
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notes = "WCCI2016",
- }
Genetic Programming entries for
Ashkan Entezari Heravi
Sheridan Houghten
Citations