ArticleNature communications2018
Intelligent image-based in situ single-cell isolation.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.
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
44 citing papers in PubMed, 1 synthesis or guideline pooled it, 95 citations in OpenAlex.
- Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments.Nature methods · 2023Guideline
- A medium throughput approach for single cell copy number variation sequencing towards efficient application in clinics.Journal of advanced research · 2026Article
- A Subphase-Labeled Mitotic Dataset for AI-powered Cell Division Analysis.Scientific data · 2026Article
- Local co-expression of GLP1R and INS in human cortical interneurons.Frontiers in endocrinology · 2026Article
- µCodes: A Universal Grid Platform for Microscale Mapping, Microscopy Navigation, and Multimodal Imaging.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Spatial proteomics in translational and clinical research.Molecular systems biology · 2025Article
- Nonviral protein cages as tools to decipher and combat viral threats.Npj viruses · 2025Review
- Recent Developments in Single-Cell Metabolomics by Mass Spectrometry─A Perspective.Journal of proteome research · 2025Review
- AI-based hardware and software tools in microscopy to boost research in immunology and virology.Frontiers in immunology · 2025Review
- SuperCUT, an unsupervised multimodal image registration with deep learning for biomedical microscopy.Briefings in bioinformatics · 2024Article
- Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes.Cancer heterogeneity and plasticity · 2024Article
- High-quality single-cell transcriptomics from ovarian histological sections during folliculogenesis.Life science alliance · 2023Article
- Constructing an In Vitro and In Vivo Flow Cytometry by Fast Line Scanning of Confocal Microscopy.Sensors (Basel, Switzerland) · 2023Article
- Article
- Correlative Fluorescence and Raman Microscopy to Define Mitotic Stages at the Single-Cell Level: Opportunities and Limitations in the AI Era.Biosensors · 2023Review
- Article
- A Device for Isolation of Selected Single Adherent Cells.BioMed research international · 2022Article
- Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine.Expert review of proteomics · 2021Review
- Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy.Journal of the Chinese Medical Association : JCMA · 2021Review
- Bridging the Brain and Data Sciences.Big data · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors at 5 institutions in 3 countries.
Funding
Abstract
Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample.
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.