Omics Research on HIV: From Pathogenesis to Treatment
A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "Human Virology and Viral Diseases".
Deadline for manuscript submissions: 31 May 2027 | Viewed by 40
Editor
Interests: HIV; antisense transcripts; HIV latency; genome informatics; bioinformatics; machine learning; computational modeling
Special Issue Information
Dear Colleagues,
HIV infection remains incurable, due in large part to the heterogeneous nature of HIV subtypes and pathogenesis. This heterogeneity spans multiple scales: at the level of individual viruses, it manifests as biased integration site selection and stochastic transcriptional activity; at a broader level, it encompasses diverse reservoir cell types, distinct anatomical sanctuaries, and subtype diversity. With this element in mind, the value of omics research in HIV becomes apparent: omics approaches enable the integration of large-scale datasets and the systematic profiling of numerous molecular features, offering a means to unravel the complex mechanistic networks underlying HIV pathogenesis as a whole. Moreover, when paired with advanced computational approaches capable of rapidly processing large datasets and uncovering patterns embedded within complex data, omics studies not only enhance the biological interpretability of findings but also contribute to the development of new antiretroviral strategies through the identification of novel drug targets and biomarkers and the refinement of clinical decision-making.
This Special Issue therefore welcomes a broad range of HIV omics studies, including but not limited to genomics, epigenomics, transcriptomics, epitranscriptomics, proteomics, and metabolomics. Studies employing multi-omics integration, metagenomics, single-cell sequencing, and spatial transcriptomics are especially encouraged. Also within scope are newly developed computational and modeling approaches for analyzing HIV omics data, the design of novel antiretroviral drugs, and strategies to improve therapeutic regimens.
Original research, reviews, short communications, and methods papers are welcome.
Dr. Heng-Chang Chen
Guest Editor
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Keywords
- HIV pathogenesis
- antiretroviral therapy and strategies
- omics and multi-omics approaches
- metagenomics
- machine learning
- single-cell sequencing
- spatial transcriptomics
- epitranscriptomics
- metabolomics
- bioinformatics
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