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.
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Heng‐Chang Chen
Łukasiewicz Research Network – PORT Polish Center for Technology Development
Journal of Translational Medicine
Łukasiewicz Research Network – PORT Polish Center for Technology Development
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Heng‐Chang Chen (Wed,) studied this question.
synapsesocial.com/papers/68a365560a429f797332b0c9 — DOI: https://doi.org/10.1186/s12967-025-06919-z
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