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Int J Biochem Cell Biol. 2009 Feb;41(2):405-13. doi: 10.1016/j.biocel.2008.09.025. Epub 2008 Oct 2.

Applications of genetic programming in cancer research.

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1
Genetics Squared Inc., 401 West Morgan Road, Ann Arbor, MI 48108, USA.

Abstract

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

PMID:
18929677
PMCID:
PMC3298968
DOI:
10.1016/j.biocel.2008.09.025
[Indexed for MEDLINE]
Free PMC Article
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