ReviewFrontiers in immunology2019
Techniques for Studying Decoding of Single Cell Dynamics.
Review in Frontiers in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed.
- Sensitivity Enhancement of Dynamic Full-Field Optical Coherence Tomography Using Ratio-Free Detection and Partial-Field Illumination for Retinal Organoid Imaging.Bioengineering (Basel, Switzerland) · 2026Article
- Oncogenic Alterations in PI3K Signaling Emulated Optogenetically Recapitulate Some Phenotypic Changes in Mammary Epithelia.ACS synthetic biology · 2026Article
- Decoding the Central Dogma: Quantitative Insights into Transcription and Translation Dynamics in the p53-Mediated DNA Damage Response.Journal of molecular biology · 2026Review
- Deciphering single-cell genomic architecture: insights into cellular heterogeneity and regulatory dynamics.Genomics & informatics · 2025Review
- Advancing outcome measure development and analytical approaches: Pain in Animals Workshop 2023.Frontiers in pain research (Lausanne, Switzerland) · 2025Review
- Advances in high throughput cell culture technologies for therapeutic screening and biological discovery applications.Bioengineering & translational medicine · 2024Review
- Cellular heterogeneity in TNF/TNFR1 signalling: live cell imaging of cell fate decisions in single cells.Cell death & disease · 2024Review
- Unraveling IFN-I response dynamics and TNF crosstalk in the pathophysiology of systemic lupus erythematosus.Frontiers in immunology · 2024Article
- Reversing pathological cell states: the road less travelled can extend the therapeutic horizon.Trends in cell biology · 2023Review
- Dynamic full-field optical coherence tomography module adapted to commercial microscopes allows longitudinal in vitro cell culture study.Communications biology · 2023Article
- Time-dependent cell-state selection identifies transiently expressed genes regulating ILC2 activation.Communications biology · 2023Article
- Interface self-referenced dynamic full-field optical coherence tomography.Biomedical optics express · 2023Article
- An optimized reporter of the transcription factor hypoxia-inducible factor 1α reveals complex HIF-1α activation dynamics in single cells.The Journal of biological chemistry · 2023Article
- Soluble cyclase-mediated nuclear cAMP synthesis is sufficient for cell proliferation.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Modeling Cellular Signaling Variability Based on Single-Cell Data: The TGFβ-SMAD Signaling Pathway.Methods in molecular biology (Clifton, N.J.) · 2023Review
- Live imaging of apoptotic signaling flow using tunable combinatorial FRET-based bioprobes for cell population analysis of caspase cascades.Scientific reports · 2022Article
- Revising immune cell coordination: Origins and importance of single-cell variation.European journal of immunology · 2022Review
- Systems approaches to investigate the role of NF-κB signaling in aging.The Biochemical journal · 2022Review
- A transcriptional biosensor to monitor single cancer cell therapeutic responses by bioluminescence microscopy.Theranostics · 2022Article
- Cell-Cell Communication Networks in Tissue: Toward Quantitatively Linking Structure with Function.Current opinion in systems biology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Cells must be able to interpret signals they encounter and reliably generate an appropriate response. It has long been known that the dynamics of transcription factor and kinase activation can play a crucial role in selecting an individual cell's response. The study of cellular dynamics has expanded dramatically in the last few years, with dynamics being discovered in novel pathways, new insights being revealed about the importance of dynamics, and technological improvements increasing the throughput and capabilities of single cell measurements. In this review, we highlight the important developments in this field, with a focus on the methods used to make new discoveries. We also include a discussion on improvements in methods for engineering and measuring single cell dynamics and responses. Finally, we will briefly highlight some of the many challenges and avenues of research that are still open.
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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.