We present serial evolutionary networks as a longitudinal representation of the mutational pathways of a viral population in a within-host environment.
In this paper, we explore the discovery power of our computational tool by taking a closer look at the generated serial evolutionary networks.
We expect an abundance of new clonal sequences from longitudinal studies, which can be used in the reconstruction of serial evolutionary networks for a much larger number of patients and can contribute to the development of tools for HIV patient surveillance and prognosis.
In their shortened form, they are unique within a sampling point, but not across the whole serial evolutionary network.
The serial evolutionary network proved to be an effective and useful tool, able to produce noteworthy results, as well as generate important and productive new lines of inquiry in the study of viral evolution.
This can be observed in all the serial evolutionary networks presented here.
In this paper, the serial evolutionary networks, which were produced by the improved method, Sliding MinPD, are presented.
The serial evolutionary networks of the 8 patients revealed different aspects of the within-host evolution of the HIV virus.
The serial evolutionary network representation allowed us to look for patterns present in the networks of the three surviving patients and absent in the other networks.
The placement of this information under the serial evolutionary networks facilitates the visual discovery of patterns and associations between the different factors affecting the within-patient evolution of HIV.
