ReviewBMB reports2020
Single-cell and spatial transcriptomics approaches of cardiovascular development and disease.
Review in BMB reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis 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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases.International journal of molecular sciences · 2024Pooled it
- Multi-Omics and Artificial Intelligence in Cardiovascular Medicine: From Mechanistic Insights to Clinical Translation.Biomedicines · 2026Review
- Single-cell insights into tumor microenvironment heterogeneity and plasticity: transforming precision therapy in gastrointestinal cancers.Journal of experimental & clinical cancer research : CR · 2025Review
- Transformative Potential of Induced Pluripotent Stem Cells in Congenital Heart Disease Research and Treatment.Children (Basel, Switzerland) · 2025Review
- Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics.Nature communications · 2025Article
- Flexible analysis of spatial transcriptomics data (FAST): a deconvolution approach.BMC bioinformatics · 2025Article
- Application of Spatial Omics in the Cardiovascular System.Research (Washington, D.C.) · 2025Review
- Single-cell and spatial transcriptomics: Discovery of human placental development and disease.FASEB bioAdvances · 2024Review
- Spot-Based Global Registration for Subpixel Stitching of Single-Molecule Resolution Images for Tissue-Scale Spatial Transcriptomics.Analytical chemistry · 2024Article
- SPADE: spatial deconvolution for domain specific cell-type estimation.Communications biology · 2024Article
- Non-Coding RNAs Regulating Mitochondrial Functions and the Oxidative Stress Response as Putative Targets against Age-Related Macular Degeneration (AMD).International journal of molecular sciences · 2023Review
- Cardiac cellular diversity and functionality in cardiac repair by single-cell transcriptomics.Frontiers in cardiovascular medicine · 2023Review
- Integrated analysis of plasma proteome and cortex single-cell transcriptome reveals the novel biomarkers during cortical aging.Frontiers in aging neuroscience · 2023Article
- Microfluidic cell sorter sample preparation for genomic assays.Biomicrofluidics · 2022Article
- High-resolution Slide-seqV2 spatial transcriptomics enables discovery of disease-specific cell neighborhoods and pathways.iScience · 2022Article
- Recent advances in spatially resolved transcriptomics: challenges and opportunities.BMB reports · 2022Review
- Echidna: integrated simulations of single-cell immune receptor repertoires and transcriptomes.Bioinformatics advances · 2022Article
- Treating Duchenne Muscular Dystrophy: The Promise of Stem Cells, Artificial Intelligence, and Multi-Omics.Frontiers in cardiovascular medicine · 2022Review
- Single-Cell RNA Sequencing (scRNA-seq) in Cardiac Tissue: Applications and Limitations.Vascular health and risk management · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advancements in the resolution and throughput of single-cell analyses, including single-cell RNA sequencing (scRNA-seq), have achieved significant progress in biomedical research in the last decade. These techniques have been used to understand cellular heterogeneity by identifying many rare and novel cell types and characterizing subpopulations of cells that make up organs and tissues. Analysis across various datasets can elucidate temporal patterning in gene expression and developmental cues and is also employed to examine the response of cells to acute injury, damage, or disruption. Specifically, scRNA-seq and spatially resolved transcriptomics have been used to describe the identity of novel or rare cell subpopulations and transcriptional variations that are related to normal and pathological conditions in mammalian models and human tissues. These applications have critically contributed to advance basic cardiovascular research in the past decade by identifying novel cell types implicated in development and disease. In this review, we describe current scRNA-seq technologies and how current scRNA-seq and spatial transcriptomic (ST) techniques have advanced our understanding of cardiovascular development and disease. [BMB Reports 2020; 53(8): 393-399].
Indexed as
Identifiers
32684243PMC7473476What 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.