# From network biology to immunity: potential longitudinal biomarkers for targeting the network topology of the HIV reservoir

## TL;DR

This paper explores how network biology can identify biomarkers for the HIV reservoir by analyzing network topology and comparing them with experimental findings.

## Contribution

The paper introduces potential longitudinal biomarkers for the HIV reservoir derived from network-based analysis.

## Key findings

- Network topology analysis can reveal functional roles in the HIV reservoir.
- Longitudinal biomarkers from network analysis are compared with experimentally derived ones.
- Graph theory concepts are applied to understand HIV reservoir network organization.

## Abstract

In the “omics” era, studies often utilize large-scale datasets, eliciting the overall functional machinery of a network’s organization. In this context, determining how to read the enormous number of interactions in a network is imperative to comprehend its functional organization. Topology is the principal attribute of any network; as such, topological properties help to elucidate the roles of entities and represent a network’s behavior. In this review, I showcase the foundational concepts involved in graph theory, which form the basis of network biology, and exemplify the application of this conceptual framework to bridge the connection between the task-evoked functional genome network of the HIV reservoir. Furthermore, I point out potential longitudinal biomarkers identified using network-based analysis and systematically compare them with other potential biomarkers identified based on experimental research with longitudinal clinical samples.