ReviewF1000Research2016
Single-cell transcriptome sequencing: recent advances and remaining challenges.
Review in F1000Research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 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
124 citing papers in PubMed.
- Bacterial Siderophore Production in Metal-Rich Environments: Underexplored Sources of Siderophores and Insights into Bioremediation.Journal of natural products · 2026Review
- scSemiPLC: a semi-supervised learning framework for annotating single-cell RNA-Seq data by generating pseudo-labels through clustering.mSystems · 2026Article
- Single-cell RNA-seq reveals the piperlongumine is a potential drug for ischemic stroke.PloS one · 2026Article
- Single-Cell Transcriptome and Microbiome Profiling Uncover Ileal Immune Impairment in Intrauterine Growth-Retarded Piglets.Current pharmaceutical design · 2026Article
- Navigating single-cell RNA-sequencing: protocols, tools, databases, and applications.Genomics & informatics · 2025Review
- Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation.PLoS computational biology · 2025Article
- Psychological stress increases skin infection through the action of TGFβ to suppress immune-acting fibroblasts.Science immunology · 2025Article
- Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives.Molecular medicine (Cambridge, Mass.) · 2025Review
- Lung Immune Cell Niches and the Discovery of New Cell Subtypes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Performance comparison of high throughput single-cell RNA-Seq platforms in complex tissues.Heliyon · 2024Article
- Binomial models uncover biological variation during feature selection of droplet-based single-cell RNA sequencing.PLoS computational biology · 2024Article
- Identifying prognostic biomarkers in oral squamous cell carcinoma: an integrated single-cell and bulk RNA sequencing study on mitophagy-related genes.Scientific reports · 2024Article
- Decoding cellular plasticity and niche regulation of limbal stem cells during corneal wound healing.Stem cell research & therapy · 2024Article
- Integrating phylogenies into single-cell RNA sequencing analysis allows comparisons across species, genes, and cells.PLoS biology · 2024Article
- An ultra high-throughput, massively multiplexable, single-cell RNA-seq platform in yeasts.Yeast (Chichester, England) · 2024Article
- Techniques for investigating lncRNA transcript functions in neurodevelopment.Molecular psychiatry · 2024Review
- Review
- Roles of Non-Coding RNA in Alzheimer's Disease Pathophysiology.International journal of molecular sciences · 2023Review
- Single-cell RNA sequencing in cornea research: Insights into limbal stem cells and their niche regulation.World journal of stem cells · 2023Review
- Single-Cell Analysis in Immuno-Oncology.International journal of molecular sciences · 2023Review
64 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
2 authors.
Funding
Abstract
Single-cell RNA-sequencing methods are now robust and economically practical and are becoming a powerful tool for high-throughput, high-resolution transcriptomic analysis of cell states and dynamics. Single-cell approaches circumvent the averaging artifacts associated with traditional bulk population data, yielding new insights into the cellular diversity underlying superficially homogeneous populations. Thus far, single-cell RNA-sequencing has already shown great effectiveness in unraveling complex cell populations, reconstructing developmental trajectories, and modeling transcriptional dynamics. Ongoing technical improvements to single-cell RNA-sequencing throughput and sensitivity, the development of more sophisticated analytical frameworks for single-cell data, and an increasing array of complementary single-cell assays all promise to expand the usefulness and potential applications of single-cell transcriptomic profiling.
Indexed as
Identifiers
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.