ReviewImmune network2026
Decoding Immune Regulation: From Genetic Variation to Mechanism Through Single-Cell Genomics.
Review in Immune network, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immune cell states are not fixed. Rather, they emerge from dynamic transcriptional programs shaped by genetic variation, cellular context, and gene regulatory networks (GRNs). Single-cell and multi-omic technologies now enable population-scale immune profiling across molecular layers, revealing that cell-to-cell transcriptional variability is a functional feature that diversifies immune responses. Distribution-aware and tensor-based analytical frameworks capture this variability beyond mean expression, resolving coordinated gene programs across cell types, individuals, and conditions. Integrating human genetics with single-cell genomics demonstrates that genetic effects on gene expression, splicing, and chromatin accessibility are highly dependent on cell type, activation state, and differentiation trajectory. These variant-level signals converge on GRNs in which key transcription factors orchestrate context-dependent immune programs. High-throughput perturbation screens enable scalable functional validation of these networks, linking genetic variation to cellular function. Together, these integrative approaches translate molecular discoveries into clinical applications, from patient stratification to therapeutic target prioritization. Emerging spatial multi-omics and
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.