Identification of quantitative trait nucleotides that regulate cancer growth: A simulation approach

Hongying Li, Bong Rae Kim, Rongling Wu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

A general growth model derived from basic cellular properties can be used to describe the dynamic process of cancer growth with mathematical equations. It has been recognized that cancer growth is under genetic control, with a multitude of interacting genes each segregating in a Mendelian fashion and displaying environmental sensitivity. In this article, we integrate the mathematical aspects of the pervasive growth model into a statistical framework for the identification of quantitative trait nucleotides that underlie cancer growth. This integrative framework is constructed with a single nucleotide polymorphism-based haplotype blocking analysis. Simulation studies have been performed to demonstrate the usefulness of the model. The proposed model provides a generic platform model for testing and detecting specific DNA sequence variants that regulates the timing of cancer emergence, growth and differentiation.

Original languageEnglish (US)
Pages (from-to)426-439
Number of pages14
JournalJournal of Theoretical Biology
Volume242
Issue number2
DOIs
StatePublished - Sep 21 2006

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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