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Omics Integration Uncovers Mechanisms Associated with HIV Viral Load and Potential Therapeutic Insights

2025-07-30 hiv aids Title + abstract only
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While antiretroviral therapy (ART) has significantly improved disease prognosis in people with HIV (PWH), understanding the biological mechanisms underlying plasma HIV-1 RNA viral load (VL) can inform additional strategies to slow HIV/AIDS disease progression. Here, we integrated multi-omic datasets and used two machine learning network biology tools (GRIN and MENTOR) to identify biological mechanisms associated with VL across 10 cohorts from multiple omics data sets. We integrated the following...

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