SVM en paralelo para optimizar el tiempo de respuesta en la predicción de co-receptores de los virus R5, X4 Y R5X4 (mutado) que causan el Sida (VIH-1) en células CD4

In particular, the R5 HIV-1 viruses use CCR5 as co-receptor for the virus entrance, the X4 virus HIV-1 use the CXCR4, while some strange viruses known as R5X4 or D-tropic, have the ability to use both co-receptors. The X4 and R5X4 viruses are associated with rapid progress in HIV-1. In this article a series of experiments will be carried out to implement a Supervised Learning Machine in Parallel that allows optimizing the response time in the prediction of co-receptors (CCR5, CXCR4) of the virus that cause AIDS (HIV-1) in CD4 cells. To implement the machine in parallel we will use Snow in R. Snow provides the support to easily execute functions in R in parallel. Most functions in parallel in Snow are variations of the standard lapply () function. To implement the functions in parallel, Snow uses a master / slave architecture where the teacher sends tasks to the workers, and the workers execute the tasks and return the results to the teacheR.