ReviewBriefings in bioinformatics2025
Applications and techniques of single-cell RNA sequencing across diverse species.
Review in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Bridging Organ-on-a-Chip and Omics: A Multi-Dimensional Frontier in Biomedical Research.Biotechnology and bioengineering · 2026Review
- scASprofiler: profiling single-cell RNA splicing with a deep convolutional generative network.Briefings in bioinformatics · 2026Article
- A Ternary Flavonoid Formulation Mitigates Fractional Radiation-Induced Brain Injury via Transcriptomic Reprogramming and Synaptic Protection.International journal of molecular sciences · 2026Article
- RAG: a regularized adaptive graph-based method for rare-cell identification from single-cell expression data.Briefings in bioinformatics · 2026Article
- CTMAP: an adversarial cross-modal learning framework for accurate and robust cell-type annotation in single-cell resolution spatial transcriptomics.Briefings in bioinformatics · 2026Article
- Immune Landscape and Tumour Heterogeneity in Ovarian Cancer: Insights From Single-Cell RNA Sequencing.Journal of cellular and molecular medicine · 2026Review
- Empowering fungal infection research with single-cell RNA sequencing.Communications biology · 2026Review
- The Paipu framework enables creation of a large-scale mammalian cancer transcriptomics atlas.bioRxiv : the preprint server for biology · 2026Article
- Integrating and mapping single-cell transcriptomics across the entire gene expression space.Briefings in bioinformatics · 2026Article
- Overcoming immune resistance in hepatocellular carcinoma: insights into mechanisms, predictive factors, and interventional strategies.Frontiers in immunology · 2026Review
- Bidirectional Mendelian Randomization and Single‑Cell RNA Sequencing Reveal an NK Cell-Mediated Causal Link Between Endometriosis and Endometrial Cancer.International journal of women's health · 2026Article
- Understanding the immune microenvironment of ovarian cancer.Frontiers in oncology · 2026Review
- Identification of Drug-resistant Cell Subpopulations in Colorectal Cancer Through Single-cell Analysis and Exploration of Potential Therapeutic Strategies.Current medicinal chemistry · 2026Article
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 ribonucleic acid sequencing (scRNA-seq) is an important tool in molecular biology, allowing transcriptomic profiling at the single-cell level. This transformative technology has provided unprecedented insights into cellular heterogeneity, lineage differentiation, and cell-type-specific gene expression patterns, significantly advancing our understanding of complex biological systems. scRNA-seq is broadly applied across various fields, including oncology, where it sheds light on intratumoral heterogeneity and precision medicine strategies, and developmental biology, where it uncovers cellular trajectories in both model and non-model organisms. Additionally, scRNA-seq has been instrumental in ecological genomics, which can help elucidate cellular responses to environmental perturbations and species interactions. Despite these advancements, several challenges remain, particularly technical and financial barriers, limiting its application to non-model organisms and tissues with complex cellular compositions. Addressing these issues will require continued innovation in single-cell isolation methods, cost-effective sequencing technologies, and sophisticated bioinformatics tools. As scRNA-seq advances, it can deepen our understanding of biological systems, with broad implications for personalized medicine, evolutionary biology, and ecological research.
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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.