ArticleMolecular biology of the cell2025
Deep learning-driven imaging of cell division and cell growth across an entire eukaryotic life cycle.
Article in Molecular biology of the cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- Love-thy-neighbor: Neural networks for tracking and lineage tracing in budding yeast.bioRxiv : the preprint server for biology · 2026Article
- Love-thy-neighbor: neural networks for tracking and lineage tracing in budding yeast.Bioinformatics advances · 2026Article
- Imaging the Entire Sexual Life Cycle of the Budding YeastBio-protocol · 2025Article
- Measuring Regulatory Network Inheritance in Dividing Yeast Cells Using Ordinary Differential Equations.bioRxiv : the preprint server for biology · 2025Article
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7 authors.
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Abstract
The life cycle of eukaryotic microorganisms involves complex transitions between states such as dormancy, mating, meiosis, and cell division, which are often studied independently from each other. Therefore, most microbial life cycles are theoretical reconstructions from partial observations of cellular states. Here we show that complete microbial life cycles can be directly and continuously studied by combining microfluidic culturing, life cycle stage-specific segmentation of micrographs, and a novel cell tracking algorithm, FIEST, based on deep learning video frame interpolation. As proof of principle, we quantitatively imaged and compared cell growth and the activity state of the cell division kinase, Cdk1, across the life cycle of
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