How to compute which genes control drug resistance dynamics
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Updated: Jun 4, 2026

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
Published on: December 9, 2015
Yunqian Guo1, Jiangtao Luo, Jianxin Wang
1Center for Computational Biology, Beijing Forestry University, Beijing 100083, China.
Abstract:
Increasing evidence shows that genes have a pivotal role in affecting the dynamic pattern of viral loads in the body of a host. By reviewing the biochemical interactions between a virus and host cells as a dynamic system, we outline a computational approach for mapping the genetic control of virus dynamics. The approach integrates differential equations (DEs) to quantify the dynamic origin and behavior of a viral infection system. It enables geneticists to generate various testable hypotheses about the genetic control mechanisms for virus dynamics and infection. The experiment designed according to this approach will also enable researchers to gain insight into the role of genes in limiting virus abundance and the dynamics of viral drug resistance, facilitating the development of personalized medicines to eliminate viral infections.
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