Discovering human immunodeficiency virus mutational pathways using temporal Bayesian networks

摘要

ObjectiveThe human immunodeficiency virus (HIV) is one of the fastest evolving organisms in the planet. Its remarkable variation capability makes HIV able to escape from multiple evolutionary forces naturally or artificially acting on it, through the development and selection of adaptive mutations. Although most drug resistance mutations have been well identified, the dynamics and temporal patterns of appearance of these mutations can still be further explored. The use of models to predict mutational pathways as well as temporal patterns of appearance of adaptive mutations could greatly benefit clinical management of individuals under antiretroviral therapy.