Current insight into HIV-1 persistence from single-cell transcriptome profiling in acutely treated cohorts of infection

Single-cell transcriptomics is a powerful technology that screens the entire transcriptome of an individual cell. When used strategically to investigate samples from cohorts of acute HIV-1 infection, this unbiased omics tool can shed light on the elusive HIV-1 reservoir and unlock strategies for cure.

Authors

Institutions

Publication Details

Journal
Current Opinion in HIV and AIDS
Published
2025-07-04
DOI
https://doi.org/10.1097/coh.0000000000000962
Primary Topic
HIV Research and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Current insight into HIV-1 persistence from single-cell transcriptome profiling in acutely treated cohorts of infection

Lakshmi Iyer, Rasmi Thomas
Current Opinion in HIV and AIDS
HIV Research and Treatment
article

Current insight into HIV-1 persistence from single-cell transcriptome profiling in acutely treated cohorts of infection

Lakshmi Iyer, Rasmi Thomas
article en

Abstract

Single-cell transcriptomics is a powerful technology that screens the entire transcriptome of an individual cell. When used strategically to investigate samples from cohorts of acute HIV-1 infection, this unbiased omics tool can shed light on the elusive HIV-1 reservoir and unlock strategies for cure.

Current Opinion in HIV and AIDSVol. 20(5)
Henry M. Jackson Foundation (US), Walter Reed Army Institute of Research (US)
Openalex Percentile: Top 82%
HIV Research and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.