ReviewCells2020
The Role of Single-Cell Technology in the Study and Control of Infectious Diseases.
Review in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
16 citing papers in PubMed.
- Confronting the known unknown: historical lessons and future strategies for Disease X.Frontiers in public health · 2026Review
- A comparative review of single-cell atlases: mapping cellular diversity across species and tissues.Cellular and molecular life sciences : CMLS · 2025Review
- Clinical application of single-cell RNA sequencing in disease and therapy.Clinical and translational medicine · 2025Review
- Multi-omics approaches: transforming the landscape of natural product isolation.Functional & integrative genomics · 2025Review
- Optimized single-cell gates for yeast display screening.Protein engineering, design & selection : PEDS · 2025Article
- Single-cell sequencing in molecular diagnostics: Transformative yet untapped potential.Frontiers in genetics · 2025Review
- Intestinal cell diversity and treatment responses in a parasitic nematode at single cell resolution.BMC genomics · 2024Article
- Waterborne pathogens detection technologies: advances, challenges, and future perspectives.Frontiers in microbiology · 2023Review
- scFeatures: multi-view representations of single-cell and spatial data for disease outcome prediction.Bioinformatics (Oxford, England) · 2022Article
- Recent developments in systems biology and genetic engineering toward design of vaccines for TB.Critical reviews in biotechnology · 2022Review
- Transcriptome Architecture of Osteoblastic Cells Infected WithFrontiers in cellular and infection microbiology · 2022Article
- Metabolic therapy and bioenergetic analysis: The missing piece of the puzzle.Molecular metabolism · 2021Review
- Pathogen detection with electrochemical biosensors: Advantages, challenges and future perspectives.Journal of electroanalytical chemistry (Lausanne, Switzerland) · 2021Review
- Johne's Disease in Dairy Cattle: An Immunogenetic Perspective.Frontiers in veterinary science · 2021Review
- Review
- Single-Cell Analysis.Cells · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advent of single-cell research in the recent decade has allowed biological studies at an unprecedented resolution and scale. In particular, single-cell analysis techniques such as Next-Generation Sequencing (NGS) and Fluorescence-Activated Cell Sorting (FACS) have helped show substantial links between cellular heterogeneity and infectious disease progression. The extensive characterization of genomic and phenotypic biomarkers, in addition to host-pathogen interactions at the single-cell level, has resulted in the discovery of previously unknown infection mechanisms as well as potential treatment options. In this article, we review the various single-cell technologies and their applications in the ongoing fight against infectious diseases, as well as discuss the potential opportunities for future development.
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What OpenQuestion holds
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.