ArticleFrontiers in molecular biosciences2020
Pinpointing Cell Identity in Time and Space.
Article in Frontiers in molecular biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 22 citations in OpenAlex.
- Editorial: Technologies for RNA Detection.Bio-protocol · 2026Article
- Divergence in cellular markers observed in single-cell transcriptomics datasets between cultured primary trabecular meshwork cells and tissues.Scientific data · 2025Article
- Need of orthogonal approaches in neurological disease modeling in mouse.Frontiers in molecular neuroscience · 2024Review
- RNA trafficking and subcellular localization-a review of mechanisms, experimental and predictive methodologies.Briefings in bioinformatics · 2023Review
- Mapping Spatiotemporal Heterogeneity in Tumor Profiles by Integrating High-Throughput Imaging and Omics Analysis.ACS omega · 2023Review
- Protocol for Classification Single-Cell PBMC Types from Pathological Samples Using Supervised Machine Learning.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Cell Heterogeneity Uncovered by Single-Cell RNA Sequencing Offers Potential Therapeutic Targets for Ischemic Stroke.Aging and disease · 2022Review
- Understanding the Transcriptomic Landscape to Drive New Innovations in Musculoskeletal Regenerative Medicine.Current osteoporosis reports · 2022Review
- Deciphering tissue structure and function using spatial transcriptomics.Communications biology · 2022Review
- Advances in endogenous RNA pull-down: A straightforward dextran sulfate-based method enhancing RNA recovery.Frontiers in molecular biosciences · 2022Article
- How a cell decides its own fate: a single-cell view of molecular mechanisms and dynamics of cell-type specification.Biochemical Society transactions · 2021Review
- Prediction of RNA subcellular localization: Learning from heterogeneous data sources.iScience · 2021Review
- Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review.Biomolecules · 2021Review
- Automated segmentation and analysis of retinal microglia within ImageJ.Experimental eye research · 2021Article
- LISA2: Learning Complex Single-Cell Trajectory and Expression Trends.Frontiers in genetics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mammalian cells display a broad spectrum of phenotypes, morphologies, and functional niches within biological systems. Our understanding of mechanisms at the individual cellular level, and how cells function in concert to form tissues, organs and systems, has been greatly facilitated by centuries of extensive work to classify and characterize cell types. Classic histological approaches are now complemented with advanced single-cell sequencing and spatial transcriptomics for cell identity studies. Emerging data suggests that additional levels of information should be considered, including the subcellular spatial distribution of molecules such as RNA and protein, when classifying cells. In this Perspective piece we describe the importance of integrating cell transcriptional state with tissue and subcellular spatial and temporal information for thorough characterization of cell type and state. We refer to recent studies making use of single cell RNA-seq and/or image-based cell characterization, which highlight a need for such in-depth characterization of cell populations. We also describe the advances required in experimental, imaging and analytical methods to address these questions. This Perspective concludes by framing this argument in the context of projects such as the Human Cell Atlas, and related fields of cancer research and developmental biology.
Indexed as
Identifiers
What Socratic 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 Socratic graph.