ReviewClinical and translational medicine2022
Single-cell RNA sequencing technologies and applications: A brief overview.
Review in Clinical and translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 730 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
730 citing papers in PubMed, 1,181 citations in OpenAlex.
- Single-cell RNA sequencing unravels mosquito biology and host-pathogen interactions.Parasites & vectors · 2026Review
- The CRABP2-MDK Signaling Axis Promotes Lung Adenocarcinoma (LUAD) Progression and Highlights Prognostic Biomarkers.Molecular carcinogenesis · 2026Article
- Spatial Proteomics as a Potential Decision-Support Layer for Early Melanoma: A Narrative Review.International journal of dermatology · 2026Review
- Article
- Integration of Single-Cell and Bulk RNA Sequencing Data to Identify Lactylation-Related Gene Signatures in Hepatic Ischemia-Reperfusion Injury Using Machine Learning Algorithms.International journal of molecular sciences · 2026Article
- Integration of Multi-Omics Data To Understand the Multifaceted Role of RAMP1 across Different Cancer Types.Cell biochemistry and biophysics · 2026Review
- Decoding cell-cell communication in spatial transcriptomics: mechanistic insights, modeling constraints, and analytical caveats.Briefings in bioinformatics · 2026Review
- bMINTY: enabling reproducible management of high-throughput sequencing analysis results and their metadata.NAR genomics and bioinformatics · 2026Article
- Single-Cell RNA sequencing identifies NAMPT as a potential therapeutic target in autoimmune uveitis.Journal of advanced research · 2026Article
- Not every gene is special: Modelling scale controls the false discovery rate when analysing high-throughput sequencing data.PLoS computational biology · 2026Article
- Integration of Bulk RNA Sequencing and Single-Cell Sequencing to Identify Prognostic Genes Associated With MCDRGs in Neuroblastoma.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Decoding the senescent endothelial landscape in ischemic stroke through single-cell and bulk RNA sequencing.Functional & integrative genomics · 2026Article
- Beyond Earth: Recent Advancements in Microgravity Biomedical and Genetic Research in Saudi Arabia.International journal of molecular sciences · 2026Review
- Single-Cell RNA Sequencing Shows Markedly Elevated Immune Cell Proportions in the Endometrium of Women with Endometriosis-A Narrative Review.International journal of molecular sciences · 2026Review
- Integrating network toxicology, machine learning, and single-cell sequencing systems to analyze autophagy core genes in lung adenocarcinoma.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- From Single-cell Heterogeneity to Regenerative-medicine Accountability: A Global Readiness Passport for Stem-Cell Products.Stem cell reviews and reports · 2026Article
- In Vitro Single-Cell Transcriptomic Profiling of Cultured Stem Cells From Apical Papilla and Dental Pulp Stem Cells: Unveiling Cellular Heterogeneity.International dental journal · 2026Article
- A scalable, low-cost, sample hashing workflow for multiomic single-cell analysis using the Seq-Well SNature protocols · 2026Review
- SKIM: A fast sketching strategy integrated with model's dynamic-feedback for large-scale single-cell transcriptomic analysis.PLoS computational biology · 2026Article
- AI-Guided Long Non-Coding RNA Target Discovery for Precision Medicine: Integrating GWAS, Multi-Omics, Experimental Validation, and RNA Therapeutics.Biomedicines · 2026Review
670 more citing papers are in PubMed but not listed here.
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 at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell RNA sequencing (scRNA-seq) technology has become the state-of-the-art approach for unravelling the heterogeneity and complexity of RNA transcripts within individual cells, as well as revealing the composition of different cell types and functions within highly organized tissues/organs/organisms. Since its first discovery in 2009, studies based on scRNA-seq provide massive information across different fields making exciting new discoveries in better understanding the composition and interaction of cells within humans, model animals and plants. In this review, we provide a concise overview about the scRNA-seq technology, experimental and computational procedures for transforming the biological and molecular processes into computational and statistical data. We also provide an explanation of the key technological steps in implementing the technology. We highlight a few examples on how scRNA-seq can provide unique information for better understanding health and diseases. One important application of the scRNA-seq technology is to build a better and high-resolution catalogue of cells in all living organism, commonly known as atlas, which is key resource to better understand and provide a solution in treating diseases. While great promises have been demonstrated with the technology in all areas, we further highlight a few remaining challenges to be overcome and its great potentials in transforming current protocols in disease diagnosis and treatment.
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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.