ReviewDisease models & mechanisms2018
Dissecting human disease with single-cell omics: application in model systems and in the clinic.
Review in Disease models & mechanisms, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed.
- The dynamic expression pattern of signaling pathways involved in early embryo development.Cell communication and signaling : CCS · 2026Article
- Immune regulation and therapeutic targets in sepsis: insights from single-cell transcriptomics.Frontiers in immunology · 2026Review
- A Systematic Overview of Single-Cell Transcriptomics Databases, their Use cases, and Limitations.ArXiv · 2024Article
- Emerging applications of single-cell profiling in precision medicine of atherosclerosis.Journal of translational medicine · 2024Review
- A systematic overview of single-cell transcriptomics databases, their use cases, and limitations.Frontiers in bioinformatics · 2024Review
- Optofluidic Flow Cytometer with In-Plane Spherical Mirror for Signal Enhancement.Sensors (Basel, Switzerland) · 2023Article
- Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States.Molecules and cells · 2023Review
- Recent Advances in Monitoring Stem Cell Status and Differentiation Using Nano-Biosensing Technologies.Nanomaterials (Basel, Switzerland) · 2022Review
- Developments of Conventional and Microfluidic Flow Cytometry Enabling High-Throughput Characterization of Single Cells.Biosensors · 2022Review
- Single-Cell Multiomics Techniques: From Conception to Applications.Frontiers in cell and developmental biology · 2022Review
- Brain Region and Cell Compartment Dependent Regulation of Electron Transport System Components in Huntington's Disease Model Mice.Brain sciences · 2021Article
- Single cell analyses to understand the immune continuum in atherosclerosis.Atherosclerosis · 2021Review
- Review
- Haematopoietic ageing through the lens of single-cell technologies.Disease models & mechanisms · 2021Review
- MyoData: An expression knowledgebase at single cell/nucleus level for the discovery of coding-noncoding RNA functional interactions in skeletal muscle.Computational and structural biotechnology journal · 2021Article
- Synergies of Systems Biology and Synthetic Biology in Human Microbiome Studies.Frontiers in microbiology · 2021Review
- Advances in Chromatin and Chromosome Research: Perspectives from Multiple Fields.Molecular cell · 2020Review
- Applying Single-Cell Analysis to Gonadogenesis and DSDs (Disorders/Differences of Sex Development).International journal of molecular sciences · 2020Review
- Single-cell RNA sequencing in cardiovascular development, disease and medicine.Nature reviews. Cardiology · 2020Review
- Advances of single-cell genomics and epigenomics in human disease: where are we now?Mammalian genome : official journal of the International Mammalian Genome Society · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Probing cellular population diversity at single-cell resolution became possible only in recent years. The popularity of single-cell 'omic' approaches, which allow researchers to dissect sample heterogeneity and cell-to-cell variation, continues to grow. With continuous technological improvements, single-cell omics are becoming increasingly prevalent and contribute to the discovery of new and rare cell types, and to the deciphering of disease pathogenesis and outcome. Animal models of human diseases have significantly facilitated our understanding of the mechanisms driving pathologies and resulted in the development of more efficient therapies. The application of single-cell omics to animal models improves the precision of the obtained insights, and brings single-cell technology closer to the clinical field. This Review focuses on the use of single-cell omics in cellular and animal models of diseases, as well as in samples from human patients. It also highlights the potential of these approaches to further improve the diagnosis and treatment of various pathologies, and includes a discussion of the advantages and remaining challenges in implementing these technologies into clinical practice.
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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.