What is it about?
Computer simulations are a valuable tool for studying disease progression. For example, past researchers have modeled Alzheimer's disease using such simulations. However, previous research has failed to incorporate the randomness inherent in all biological systems. Presented in the paper is a model of Alzheimer's disease progression which includes elements of randomness to improve model accuracy.
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Why is it important?
Alzheimer's disease is the leading cause of Dementia and its prevalence continues to increase. Currently, there are limited treatment options available for Alzheimer's disease. Additionally, the existing treatments are generally designed to manage symptoms not address the disease itself. The process of researching treatments is a time-consuming and expensive one. However, mathematical models of diseases can help cheaply and rapidly guide research towards successful pathways. Generally, the more biologically accurate the model the better, the mathematical model of Alzheimer's disease I created incorporates the randomness associated with biological processes, which previous models have not included.
Perspectives
The fields of computational biology and systems biology are growing rapidly and it is an honor to have a chance to build off of the work of others in the fields and contribute myself. I hope that this article raises awareness of the potential utility of mathematical models in biology and medicine.
Meaghan Parks
Case Western Reserve University
Read the Original
This page is a summary of: Stochastic model of Alzheimer’s disease progression using two-state Markov chains, PLoS ONE, January 2024, PLOS,
DOI: 10.1371/journal.pone.0295578.
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