2025/08/13 by Heng‐Chang Chen · 1 voice
Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · Physics and Astronomy · #Bioinformatics and Genomic Networks #HIV Research and Treatment #Complex Network Analysis Techniques
paper · pdf · doi:10.1186/s12967-025-06919-z
openalex publication_date 2025/08/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
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.