An Empirical Model Describing the Evolution of Cancerous Cells
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Date
2015-03-25
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Abstract
The purpose of this study was to produce a computational
model that can simulate the evolution of cancer. It is well
known that cancerous cells result from accumulated mutations
in genes that cause the cells to divide much more frequently
than ordinary cells. Previous simulations that this model is
based on have used hypothetical sets of genes. What sets the
model presented in this study apart is that it uses genomes
from melanoma cases to predict how much a cell with a certain
set of mutations will divide. Since the model is based on real
world data instead of theoretical genes it should produce a
much more accurate model. Hopefully, this model will be able
to provide a better understanding of how cancers develop over
time and will help determine which genes are significant in
various types of cancer. This model can potentially be used to
determine which genes to target with drugs.
Description
Biological Sciences (The Ohio State University Denman Undergraduate Research Forum)
Keywords
Cancer, simulation, kernal density estimation, genome, melanoma, bioinformatics