ArticleBriefings in bioinformatics2021
Single-cell multi-omics sequencing: application trends, COVID-19, data analysis issues and prospects.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
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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, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Bibliometric and visual analysis of single-cell multiomics in neurodegenerative disease arrest studies.Frontiers in neurology · 2024Pooled it
- Advances in Oral Cavity Stem Cell Research Revealed through Multi-omics Analysis.Stem cell reviews and reports · 2026Review
- The spatiotemporal dynamic evolution of post-stroke neuroinflammation: energy metabolism mechanisms of acute response and chronic progression.Frontiers in pharmacology · 2026Review
- APDCA: An accurate and effective method for predicting associations between RBPs and AS-events during epithelial-mesenchymal transition.PLoS computational biology · 2025Article
- Severity-specific immune landscape of COVID-19 revealed by single-cell sequencing.Scientific reports · 2025Article
- Cell-cell communication: new insights and clinical implications.Signal transduction and targeted therapy · 2024Review
- Metacell-based differential expression analysis identifies cell type specific temporal gene response programs in COVID-19 patient PBMCs.NPJ systems biology and applications · 2024Article
- Stroma-associated FSTL3 is a factor of calcium channel-derived tumor fibrosis.Scientific reports · 2023Article
- ChatGPT, GPT-4, and Other Large Language Models: The Next Revolution for Clinical Microbiology?Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Advancement of Computational Design Drug Delivery System in COVID-19: Current Updates and Future Crosstalk- A Critical update.Infectious disorders drug targets · 2023Article
- An Analysis Regarding the Association Between the Nuclear Pore Complex (NPC) and Hepatocellular Carcinoma (HCC).Journal of hepatocellular carcinoma · 2023Article
- Density-based detection of cell transition states to construct disparate and bifurcating trajectories.Nucleic acids research · 2022Article
- Single-cell RNA-sequencing of zebrafish hair cells reveals novel genes potentially involved in hearing loss.Cellular and molecular life sciences : CMLS · 2022Article
- Multiomics integration-based molecular characterizations of COVID-19.Briefings in bioinformatics · 2022Review
- Computational anti-COVID-19 drug design: progress and challenges.Briefings in bioinformatics · 2022Review
- Computational solutions for spatial transcriptomics.Computational and structural biotechnology journal · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Single-cell sequencing is a biotechnology to sequence one layer of genomic information for individual cells in a tissue sample. For example, single-cell DNA sequencing is to sequence the DNA from every single cell. Increasing in complexity, single-cell multi-omics sequencing, or single-cell multimodal omics sequencing, is to profile in parallel multiple layers of omics information from a single cell. In practice, single-cell multi-omics sequencing actually detects multiple traits such as DNA, RNA, methylation information and/or protein profiles from the same cell for many individuals in a tissue sample. Multi-omics sequencing has been widely applied to systematically unravel interplay mechanisms of key components and pathways in cell. This survey overviews recent developments in single-cell multi-omics sequencing, and their applications to understand complex diseases in particular the COVID-19 pandemic. We also summarize machine learning and bioinformatics techniques used in the analysis of the intercorrelated multilayer heterogeneous data. We observed that variational inference and graph-based learning are popular approaches, and Seurat V3 is a commonly used tool to transfer the missing variables and labels. We also discussed two intensively studied issues relating to data consistency and diversity and commented on currently cared issues surrounding the error correction of data pairs and data imputation methods. The survey is concluded with some open questions and opportunities for this extraordinary field.
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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.