ReviewFrontiers in cell and developmental biology2022
Advances in Single-Cell Multi-Omics and Application in Cardiovascular Research.
Review in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Prioritizing Discovery and Advancements in Arrhythmia Therapies: NIH/NHLBI Workshop.JACC. Clinical electrophysiology · 2026Review
- Multi-Omics Analysis Identified ADAM7 as a Biomarker and Therapeutic Target for End-Stage Renal Disease.Kidney & blood pressure research · 2026Article
- Aging of the human eye lens: Epigenetic landscape and therapeutic targets in age‑related cataracts (Review).International journal of molecular medicine · 2025Review
- Kidney diseases and single-cell sequencing research: a bibliometric analysis from 2015 to 2024.Renal failure · 2025Review
- Recent Developments in Single-Cell Metabolomics by Mass Spectrometry─A Perspective.Journal of proteome research · 2025Review
- Applications of Single-Cell Omics Technologies for Induced Pluripotent Stem Cell-Based Cardiovascular Research.International journal of stem cells · 2025Review
- The Interplay Between Immunity, Inflammation and Endothelial Dysfunction.International journal of molecular sciences · 2025Review
- Mechanisms regulating vascular and lymphatic regeneration in the heart after myocardial infarction.The Journal of pathology · 2023Review
- Tumor-associated macrophages: Prognostic and therapeutic targets for cancer in humans and dogs.Frontiers in immunology · 2023Review
- Review
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
With the development of ever more powerful and versatile high-throughput sequencing techniques and innovative ways to capture single cells, mapping the multicellular tissues at the single-cell level is becoming routine practice. However, it is still challenging to depict the epigenetic landscape of a single cell, especially the genome-wide chromatin accessibility, histone modifications, and DNA methylation. We summarize the most recent methodologies to profile these epigenetic marks at the single-cell level. We also discuss the development and advancement of several multi-omics sequencing technologies from individual cells. Advantages and limitations of various methods to compare and integrate datasets obtained from different sources are also included with specific practical notes. Understanding the heart tissue at single-cell resolution and multi-modal levels will help to elucidate the cell types and states involved in physiological and pathological events during heart development and disease. The rich information produced from single-cell multi-omics studies will also promote the research of heart regeneration and precision medicine on heart diseases.
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.