ReviewHaematologica2025
Emerging technologies of single-cell multi-omics.
Review in Haematologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Clonal Metamorphosis: Deconstructing MPN Evolution with Single-Cell and Spatial Multi-Omics.Clinical and experimental medicine · 2026Review
- How biological sex shapes differences in immune responses to infection.Biology of sex differences · 2026Article
- Research progress in single‑cell omics technologies for kidney disease (Review).International journal of molecular medicine · 2026Review
- Subcellular transcriptome sequencing with single cell APEX-seq identifies regulators of cell-cell interactions.bioRxiv : the preprint server for biology · 2026Article
- Decoding the archipelago: single-cell biomarkers rechart the molecular geography of acute myeloid leukemia.Cell communication and signaling : CCS · 2026Review
- Multi-omics integration in deciphering non-small cell lung cancer drug resistance: current status, challenges, and future prospects.Hereditas · 2026Review
- Integrating single-cell and spatial multi-omics for precision oncology: from tumor ecosystems to clinical decision-making.Frontiers in oncology · 2026Review
- Epigenetic regulation in medulloblastoma: from tumor heterogeneity to diagnostic, prognostic, and translational applications.Frontiers in molecular neuroscience · 2026Review
- How to Read a Next-Generation Sequencing Report for AML and MDS? What Hematologists Need to Know.Journal of clinical medicine · 2025Review
- Review
- Single-cell multi-omics in biliary tract cancers: decoding heterogeneity, microenvironment, and treatment strategies.Molecular biomedicine · 2025Review
- Dietary microbes and functional dyspepsia: modulating the gut microecology for therapeutic benefit.Frontiers in nutrition · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The heterogeneity of the hematopoietic system was largely veiled by traditional bulk sequencing methods, which measure the averaged signals from mixed cellular populations. In contrast, single-cell sequencing has enabled the direct measurement of individual signals from each cell, significantly enhancing our ability to unveil such heterogeneity. Building on these advances, numerous single-cell multi-omics techniques have been developed into high-throughput, routinely accessible platforms, delineating the precise relationships among different layers of the central dogma in molecular biology. These technologies have uncovered the intricate landscape of genetic clonality and transcriptional heterogeneity in both normal and malignant hematopoietic systems, highlighting their roles in differentiation, disease progression, and therapy resistance. This review aims to provide a brief overview of the principles of single-cell technologies, their historical development, and a subset of ever-expanding multi-omics tools, emphasizing the specific research questions that inspired their creation. Amidst the evolving landscape of single-cell multi-omics technologies, our main objective is to guide investigators in selecting the most suitable platforms for their research needs.
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.