ReviewGenomics, proteomics & bioinformatics2023
Decoding Human Biology and Disease Using Single-cell Omics Technologies.
Review in Genomics, proteomics & bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Using Disease-Agnostic Genomic Liquid Biopsy in Complex Diagnoses: Real-Life Example of cfChIP-Seq in a Fever of Unknown Origin.JCO precision oncology · 2026Article
- Editorial for Special Issue "Technological Advances Around Next-Generation Sequencing".Current issues in molecular biology · 2026Article
- Computational Analyses and Challenges of Single-cell ATAC-seq.Genomics, proteomics & bioinformatics · 2025Review
- Plate-based 10X Genomics-compatible single-cell RNA-sequencing based on Smart-seq3xpress.BMC genomics · 2025Article
- From Multi-omics To Personalized Training: The Rise of Enduromics and Resistomics.Sports medicine - open · 2025Article
- Exploring T Cell and NK Cell Involvement in Ankylosing Spondylitis Through Single-Cell Sequencing.Journal of cellular and molecular medicine · 2024Article
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
No grant is acknowledged in the PubMed record.
Abstract
Over the past decade, advances in single-cell omics (SCO) technologies have enabled the investigation of cellular heterogeneity at an unprecedented resolution and scale, opening a new avenue for understanding human biology and disease. In this review, we summarize the developments of sequencing-based SCO technologies and computational methods, and focus on considerable insights acquired from SCO sequencing studies to understand normal and diseased properties, with a particular emphasis on cancer research. We also discuss the technological improvements of SCO and its possible contribution to fundamental research of the human, as well as its great potential in clinical diagnoses and personalized therapies of human disease.
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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.