ReviewNature reviews. Genetics2013
Single-cell sequencing-based technologies will revolutionize whole-organism science.
Review in Nature reviews. Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 602 papers, 2 of them syntheses that pooled it.
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
602 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Multi-omics and high-spatial-resolution omics: deciphering complexity in neurological disorders.GigaScience · 2025Pooled it
- Uncovering the research evolution and hotspots of metabolism in renal cell carcinoma over the last decade.Frontiers in oncology · 2025Pooled it
- Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.Methods in molecular biology (Clifton, N.J.) · 2027Article
- A Method for Imputing scRNA-seq Data Based on Mobile Graph Convolutional Generative Adversarial Networks.Biochemical genetics · 2026Article
- Bridging Organ-on-a-Chip and Omics: A Multi-Dimensional Frontier in Biomedical Research.Biotechnology and bioengineering · 2026Review
- A systematic study of WGA strategies for enhanced STR and SNP genotyping on trace DNA.International journal of legal medicine · 2026Article
- scLGGCL: Label-Guided Graph Contrastive Learning for Single-Cell Fusion Clustering.Interdisciplinary sciences, computational life sciences · 2026Article
- A pre-trained large generative model for translating single-cell transcriptomes to proteomes.Nature biomedical engineering · 2026Article
- Protocol for the enrichment of endosteal and periosteal mesenchymal cells from murine bone for single-cell transcriptome analysis.STAR protocols · 2026Article
- A particle-resolved framework for quantifying microbial colonization and vector risk on environmental microplastics.Eco-Environment & Health · 2026Article
- What Are the Practical Applications of Single-Cell Proteomics?Proteomes · 2026Article
- Differential expression analysis in single-cell and spatial RNA-seq without model assumptions.Cell reports methods · 2026Article
- Loss of Chromosome Y Associates With Altered Immune Cell Trajectories and X-Inactivation Features.Aging cell · 2026Article
- DGM: deep graph clustering with mincut for analysis of single-cell transcriptomics.BMC genomics · 2026Article
- A multimodal spatial atlas of transcriptomic, morphological, and electrophysiological cell type densities in the mouse brain.PLoS computational biology · 2026Article
- Breast Cancer Brain Metastases: Current Understanding and Future Directions.Current oncology reports · 2026Review
- Single-Cell Mapping Reveals MIF-Centered Immunoregulatory Networks in Colorectal Cancer.International journal of molecular sciences · 2026Article
- scSuperAnnotator: a platform for benchmarking comparison and visualizing automated cellular annotation methods for scRNA-seq data.Nucleic acids research · 2026Article
- Direct and indirect neurogenesis from radial glial progenitor cell clones in the mouse neocortex.The EMBO journal · 2026Article
- Next-Generation Sequencing Dataset Downloader and In Silico Sequence Mining: Graphical-User-Interface-Based Tools for Accessible, Multiprobe Target Mining in Next-Generation Sequencing Data.Computational and structural biotechnology journal · 2026Article
542 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The unabated progress in next-generation sequencing technologies is fostering a wave of new genomics, epigenomics, transcriptomics and proteomics technologies. These sequencing-based technologies are increasingly being targeted to individual cells, which will allow many new and longstanding questions to be addressed. For example, single-cell genomics will help to uncover cell lineage relationships; single-cell transcriptomics will supplant the coarse notion of marker-based cell types; and single-cell epigenomics and proteomics will allow the functional states of individual cells to be analysed. These technologies will become integrated within a decade or so, enabling high-throughput, multi-dimensional analyses of individual cells that will produce detailed knowledge of the cell lineage trees of higher organisms, including humans. Such studies will have important implications for both basic biological research and medicine.
Indexed as
Identifiers
23897237What 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.