ReviewNature biotechnology2016
Challenges in long-term imaging and quantification of single-cell dynamics.
Review in Nature biotechnology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 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
108 citing papers in PubMed.
- Towards Improving Embryo Prioritization: Parallel Next Generation Sequencing of DNA and RNA from a Single Trophectoderm Biopsy.Scientific reports · 2019Trial
- Quantitative imaging of dynamic processes in intestinal organoids.Nature protocols · 2026Review
- Bone marrow-inspired DLL1-presenting microparticles enhance asymmetric division and maintenance of mouse hematopoietic stem and progenitor cells.Stem cell reports · 2026Article
- PROFET predicts continuous gene expression dynamics from scRNA-seq data to elucidate heterogeneity of cancer treatment responses.Cell systems · 2026Article
- Development of a universal imaging "phenome" using shape, appearance and motion (SAM) features and the SAM Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- A novel attention mechanism for noise-adaptive and robust segmentation of microtubules in microscopy images.BMC bioinformatics · 2026Article
- Suggested experimental design and computational modeling to infer single-cell lipid dynamics from a single destructive measurement.iScience · 2026Article
- Photoclickable Halotag ligands for spatiotemporal multiplexed protein labeling on living cells.RSC chemical biology · 2026Article
- Semi-automatic geometrical reconstruction and analysis of filopodia dynamics in 4D two-photon microscopy images.BMC bioinformatics · 2026Article
- Multi-parameter fluorescence lifetime imaging for high-noise neuroscience applications.Biomedical optics express · 2026Article
- Artificial Neural Networks for Bioimage Analysis.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Design principles of gene circuits for longevity.Trends in cell biology · 2025Review
- Electrochemiluminescence Discloses Active Intermediates in Oxygen Evolution Reactions of Metal-Organic Framework.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Near-zero photon bioimaging by fusing deep learning and ultralow-light microscopy.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- LivecellX: A Scalable Deep Learning Framework for Single-Cell Object-Oriented Analysis in Live-Cell Imaging.bioRxiv : the preprint server for biology · 2025Article
- Distinct actin microfilament localization during early cell plate formation through deep learning-based image restoration.Plant cell reports · 2025Article
- Ultrabright and ultrafast afterglow imaging in vivo via nanoparticles made of trianthracene derivatives.Nature biomedical engineering · 2025Article
- Multimodal Nanoplasmonic and Fluorescence Imaging for Simultaneous Monitoring of Single-Cell Secretory and Intracellular Dynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes.Communications biology · 2025Article
- Genetically encoded protein oscillators for FM streaming of single-cell data.bioRxiv : the preprint server for biology · 2025Article
48 more citing papers are in PubMed but not listed here.
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
Continuous analysis of single cells, over several cell divisions and for up to weeks at a time, is crucial to deciphering rare, dynamic and heterogeneous cell responses, which would otherwise be missed by population or single-cell snapshot analysis. Although the field of long-term single-cell imaging, tracking and analysis is constantly advancing, several technical challenges continue to hinder wider implementation of this important approach. This is a particular problem for mammalian cells, where in vitro observation usually remains the only possible option for uninterrupted long-term, single-cell observation. Efforts must focus not only on identifying and maintaining culture conditions that support normal cellular behavior while allowing high-resolution imaging over time, but also on developing computational methods that enable semiautomatic analysis of the data. Solutions in microscopy hard- and software, computer vision and specialized theoretical methods for analysis of dynamic single-cell data will enable important discoveries in biology and beyond.
Indexed as
Identifiers
27824848What 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.