ReviewMolecular aspects of medicine2018
High-dimension single-cell analysis applied to cancer.
Review in Molecular aspects of medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Technological synergy and convergent innovation: evolutionary trajectories of AI-integrated multi-omics in cancer research and clinical translation (2015-2024).Discover oncology · 2026Article
- Single-cell technologies in multiple myeloma: new insights into disease pathogenesis and translational implications.Biomarker research · 2023Review
- Single-Cell Analysis in Immuno-Oncology.International journal of molecular sciences · 2023Review
- Applying high-dimensional single-cell technologies to the analysis of cancer immunotherapy.Nature reviews. Clinical oncology · 2021Review
- Lymphoma Heterogeneity Unraveled by Single-Cell Transcriptomics.Frontiers in immunology · 2021Review
- A single-cell survey of cellular hierarchy in acute myeloid leukemia.Journal of hematology & oncology · 2020Article
- Leveraging Single-Cell RNA Sequencing Experiments to Model Intratumor Heterogeneity.JCO clinical cancer informatics · 2019Article
- 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
3 authors.
Funding
Abstract
High-dimension single-cell technology is transforming our ability to study and understand cancer. Numerous studies and reviews have reported advances in technology development. The biological insights gleaned from single-cell technology about cancer biology are less reviewed. Here we focus on research studies that illustrate novel aspects of cancer biology that bulk analysis could not achieve, and discuss the fresh insights gained from the application of single-cell technology across basic and clinical cancer studies.
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.