ReviewHuman vaccines & immunotherapeutics2023
Statistical and machine learning methods for immunoprofiling based on single-cell data.
Review in Human vaccines & immunotherapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed.
- Perioperative pembrolizumab in early-stage non-small cell lung cancer (NSCLC): conventional and distribution-based immune profiling of the tumor microenvironment and peripheral circulation.Journal for immunotherapy of cancer · 2025Trial
- T cell immunomonitoring: a comparative analysis of traditional and novel methods to quantify and characterize human antigen-specific T cells.Nature protocols · 2026Review
- cytoGPNet: Enhancing clinical outcome prediction accuracy using longitudinal cytometry data in small cohort studies.Patterns (New York, N.Y.) · 2025Article
- Editorial to special issue "The power of immunoprofiling supported by computational data integration and machine learning".Human vaccines & immunotherapeutics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Immunoprofiling has become a crucial tool for understanding the complex interactions between the immune system and diseases or interventions, such as therapies and vaccinations. Immune response biomarkers are critical for understanding those relationships and potentially developing personalized intervention strategies. Single-cell data have emerged as a promising source for identifying immune response biomarkers. In this review, we discuss the current state-of-the-art methods for immunoprofiling, including those for reducing the dimensionality of high-dimensional single-cell data and methods for clustering, classification, and prediction. We also draw attention to recent developments in data integration.
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Registered trials
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 OpenQuestion graph.