ReviewExperimental & molecular medicine2020
Human Cell Atlas and cell-type authentication for regenerative medicine.
Review in Experimental & molecular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 27 citations in OpenAlex.
- Comparison of single-cell long-read and short-read transcriptome sequencing via cDNA molecule matching: quality evaluation of the MAS-ISO-seq approach.NAR genomics and bioinformatics · 2025Article
- Sketching T cell atlases in the single-cell era: challenges and recommendations.Immunology and cell biology · 2025Review
- A single-cell transposable element atlas of human cell identity.Cell reports methods · 2025Article
- Advances in single-cell omics and multiomics for high-resolution molecular profiling.Experimental & molecular medicine · 2024Review
- Article
- scROSHI: robust supervised hierarchical identification of single cells.NAR genomics and bioinformatics · 2023Article
- Transcription factors and splice factors - interconnected regulators of stem cell differentiation.Current stem cell reports · 2023Article
- Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease.Communications biology · 2023Article
- Prospects of Using Protein Engineering for Selective Drug Delivery into a Specific Compartment of Target Cells.Pharmaceutics · 2023Review
- Article
- Engineering the next generation of cell-based therapeutics.Nature reviews. Drug discovery · 2022Review
- Human pluripotent stem cell registry: Operations, role and current directions.Cell proliferation · 2022Review
- Understanding the Transcriptomic Landscape to Drive New Innovations in Musculoskeletal Regenerative Medicine.Current osteoporosis reports · 2022Review
- An integrative proteomics method identifies a regulator of translation during stem cell maintenance and differentiation.Nature communications · 2021Article
- Single-Cell Toolkits Opening a New Era for Cell Engineering.Molecules and cells · 2021Review
- Using Cell Type-Specific Genes to Identify Cell-Type Transitions Between DifferentFrontiers in cell and developmental biology · 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 3 countries.
Funding
Abstract
In modern biology, the correct identification of cell types is required for the developmental study of tissues and organs and the production of functional cells for cell therapies and disease modeling. For decades, cell types have been defined on the basis of morphological and physiological markers and, more recently, immunological markers and molecular properties. Recent advances in single-cell RNA sequencing have opened new doors for the characterization of cells at the individual and spatiotemporal levels on the basis of their RNA profiles, vastly transforming our understanding of cell types. The objective of this review is to survey the current progress in the field of cell-type identification, starting with the Human Cell Atlas project, which aims to sequence every cell in the human body, to molecular marker databases for individual cell types and other sources that address cell-type identification for regenerative medicine based on cell data guidelines.
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.