ReviewInnovation (Cambridge (Mass.))2022
Single-cell technologies: From research to application.
Review in Innovation (Cambridge (Mass.)), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 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
71 citing papers in PubMed.
- SKIM: A fast sketching strategy integrated with model's dynamic-feedback for large-scale single-cell transcriptomic analysis.PLoS computational biology · 2026Article
- Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.Journal of ovarian research · 2026Review
- Protocol for culture, drug treatment, and dissociation of patient-derived 3D ovarian cancer microspheroids for flow cytometry.STAR protocols · 2026Article
- Benchmarking the prediction of responding cells to perturbations affecting both gene expression and cellular abundance using scRNA sequencing.Scientific reports · 2026Article
- Revolutionizing Stem Cell Sorting with Machine Learning: A Review of Trends, Tools, and Future Directions.Iranian journal of medical sciences · 2026Review
- Spatial heterogeneity of MDSCs mediated by ANXA1-FPRs signaling drives immune suppression in OSCC progression.Nature communications · 2026Article
- stSCI: A multi-task learning framework for integrative analysis of single-cell and spatial transcriptomics data.Innovation (Cambridge (Mass.)) · 2026Article
- Exploring phenotype-related single-cells through attention-enhanced representation learning.Genome medicine · 2026Article
- Synthetic lethality in cancer therapy: Mechanisms, models and clinical translation for overcoming therapeutic resistance.Clinical and translational medicine · 2026Review
- Microbial Omics Analysis for Multispecies Symbioses in Staple and Traditional Fermented Foods.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Productive chaos and precision engineering: decoupling discovery from manufacturing to revolutionize plant-inspired therapeutics.Frontiers in plant science · 2026Article
- Pygmy sperm whale multi-omics data reveal hypoxia adaptations in deep-diving cetaceans.BMC biology · 2025Article
- Systematically Revealing Quantitative Multi-Target Integrative Effects of Plants With Artificial Intelligence Method.Plant biotechnology journal · 2025Article
- The ANTsX ecosystem for mapping the mouse brain.Nature communications · 2025Article
- Multi-omics strategies for biomarker discovery and application in personalized oncology.Molecular biomedicine · 2025Review
- ResNet50 and Single-Cell Multi-Omics analysis identify key cellular and molecular features in pediatric acute lymphoblastic leukemia.Annals of hematology · 2025Article
- Review
- BestopCloud: an integrated one-stop solution for single-cell RNA sequencing data analysis.BMC genomics · 2025Article
- Single-cell profiling reveals immunoregulation of artemisinin on CD8Innovation (Cambridge (Mass.)) · 2025Article
- Article
11 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
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, more and more single-cell technologies have been developed. A vast amount of single-cell omics data has been generated by large projects, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality control, clustering, cell-type annotation, developmental inference, cell-cell transition, cell-cell interaction, and spatial analysis are developed. With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence, the molecular landscape at the single-cell level can be revealed. With spatial transcriptomics and single-cell multi-omics, even the spatial dynamic multi-level regulatory mechanisms can be deciphered. Such single-cell technologies have many successful applications in oncology, assisted reproduction, embryonic development, and plant breeding. We not only review the experimental and bioinformatics methods for single-cell research, but also discuss their applications in various fields and forecast the future directions for single-cell technologies. We believe that spatial transcriptomics and single-cell multi-omics will become the next booming business for mechanism research and commercial industry.
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.