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Population genetics models for the statistics of DNA samples under different demographic scenarios - Maximum likelihood versus approximate methods

Andrzej PolańskiMarek Kimmel — 2003

International Journal of Applied Mathematics and Computer Science

The paper reviews the basic mathematical methodology of modeling neutral genetic evolution, including the statistics of the Fisher-Wright process, models of mutation and the coalescence method under various demographic scenarios. The basic approach is the use of maximum likelihood techniques. However, due to computational problems, intuitive or approximate methods are also of great importance.

Stochastic models of progression of cancer andtheir use in controlling cancer-related mortality

Marek KimmelOlga Gorlova — 2003

International Journal of Applied Mathematics and Computer Science

A construction of a realistic statistical model of lung cancer risk and progression is proposed. The essential elements of the model are genetic and behavioral determinants of susceptibility, progression of the disease from precursor lesions through early (localized) tumors to disseminated disease, detection by various modalities, and medical intervention. Using model estimates as a foundation, mortality reduction caused by early-detection and intervention programs can be predicted under different...

Reaction-Difusion Model of Early Carcinogenesis: The Effects of Influx of Mutated Cells

Anna Marciniak-CzochraMarek Kimmel — 2008

Mathematical Modelling of Natural Phenomena

In this paper we explore a new model of field carcinogenesis, inspired by lung cancer precursor lesions, which includes dynamics of a spatially distributed population of pre-cancerous cells , constantly supplied by an influx of mutated normal cells. Cell proliferation is controlled by growth factor molecules bound to cells, . Free growth factor molecules are produced by precancerous cells and may diffuse before they become bound to other cells. The purpose of modelling is to investigate the existence...

Sampling properties of estimators of nucleotide diversity at discovered SNP sites

Alexander RenwickPenelope BonnenDimitra TrikkaDavid NelsonRanajit ChakrabortyMarek Kimmel — 2003

International Journal of Applied Mathematics and Computer Science

SNP sites are generally discovered by sequencing regions of the human genome in a limited number of individuals. This may leave SNP sites present in the region, but containing rare mutant nucleotides, undetected. Consequently, estimates of nucleotide diversity obtained from assays of detected SNP sites are biased. In this research we present a statistical model of the SNP discovery process, which is used to evaluate the extent of this bias. This model involves the symmetric Beta distribution of...

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