title: How to compute which genes control drug resistance dynamics.
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.
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing 100083, China.
authors.forename: Yunqian
authors.initials: Y
authors.lastname: Guo
authors.forename: Jiangtao
authors.initials: J
authors.lastname: Luo
authors.forename: Jianxin
authors.initials: J
authors.lastname: Wang
authors.forename: Yaqun
authors.initials: Y
authors.lastname: Wang
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D003198:Computer Simulation; D024882:Drug Resistance, Viral / Q000235:genetics*; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D019562:Viral Load / Q000235:genetics*; D014777:Virus Diseases / Q000188:drug therapy*