ArticleNature communications2022
Enabling reactive microscopy with MicroMator.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 39 citations in OpenAlex.
- DySTrack - a modular smart microscopy tool for live tracking of dynamic samples on modern commercial microscopes.Journal of cell science · 2026Article
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- ClearScope: A Fully Integrated Light-Sheet Theta Microscope for Sub-Micron-Resolution Imaging Without Lateral Size Constraints.Journal of imaging · 2026Article
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- Single-cell analysis and control of microbial systems using optogenetics.Current opinion in microbiology · 2026Review
- A flexible framework for automated STED super-resolution microscopy.Scientific reports · 2026Article
- Self-Driving Microscopes: AI Meets Super-Resolution Microscopy.Small methods · 2026Review
- Predicting neuronal firing from calcium imaging using a control theoretic approach.PLoS computational biology · 2025Article
- Image-guided optogenetic spatiotemporal tissue patterning using μPatternScope.Nature communications · 2024Article
- The rise of data-driven microscopy powered by machine learning.Journal of microscopy · 2024Article
- Live-cell imaging powered by computation.Nature reviews. Molecular cell biology · 2024Review
- Deep model predictive control of gene expression in thousands of single cells.Nature communications · 2024Article
- Harnessing artificial intelligence to reduce phototoxicity in live imaging.Journal of cell science · 2024Article
- Live-cell imaging in the deep learning era.Current opinion in cell biology · 2023Review
- Light-sheets and smart microscopy, an exciting future is dawning.Communications biology · 2023Review
- Data-driven microscopy allows for automated context-specific acquisition of high-fidelity image data.Cell reports methods · 2023Article
- An open-source microscopy framework for simultaneous control of image acquisition, reconstruction, and analysis.HardwareX · 2023Article
- An optogenetic toolkit for light-inducible antibiotic resistance.Nature communications · 2023Article
- Fast4DReg - fast registration of 4D microscopy datasets.Journal of cell science · 2023Article
- Analysis and design of single-cell experiments to harvest fluctuation information while rejecting measurement noise.Frontiers in cell and developmental biology · 2023Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microscopy image analysis has recently made enormous progress both in terms of accuracy and speed thanks to machine learning methods and improved computational resources. This greatly facilitates the online adaptation of microscopy experimental plans using real-time information of the observed systems and their environments. Applications in which reactiveness is needed are multifarious. Here we report MicroMator, an open and flexible software for defining and driving reactive microscopy experiments. It provides a Python software environment and an extensible set of modules that greatly facilitate the definition of events with triggers and effects interacting with the experiment. We provide a pedagogic example performing dynamic adaptation of fluorescence illumination on bacteria, and demonstrate MicroMator's potential via two challenging case studies in yeast to single-cell control and single-cell recombination, both requiring real-time tracking and light targeting at the single-cell level.
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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.