Evolved neural networks for HIV-1 co-receptor identification

HIV-1 infects a variety of cell types such as macrophages, T-cells and dendritic cells by expressing different chemokine receptors. R5 HIV-1 viruses use the CCR5 co-receptor for entry, X4 viruses use the CXCR4 co-receptor, and several viral strains make use of both co-receptors (a so-called “dual tropic” or R5X4 virus). Both X4 and R5X4 viruses are associated with late stage rapid progression to AIDS. It remains difficult to identify viral co-receptor type in advance of treatment, especially the R5X4 variety. In this paper we extended previous work to classify HIV-1 tropism using evolved neural networks and a larger set of HIV-1 sequences and features to improve overall classification accuracy.