title: Identification of quantitative trait nucleotides that regulate cancer growth: a simulation approach.
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.
authors.affiliation: Department of Statistics, University of Florida, Gainesville, FL 32611, USA.
authors.forename: Hongying
authors.initials: H
authors.lastname: Li
authors.forename: Bong-Rae
authors.initials: BR
authors.lastname: Kim
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D004843:Epistasis, Genetic; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D008957:Models, Genetic; D009010:Monte Carlo Method; D009369:Neoplasms / Q000235:genetics* / Q000473:pathology; D040641:Quantitative Trait Loci