ArticleNature communications2020
A convolutional neural network segments yeast microscopy images with high accuracy.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.
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Who cites it
80 citing papers in PubMed.
- Single-cell imaging reveals a key role of Bck2 in yeast cell size adaptation to nutrient challenges.The Journal of cell biology · 2026Article
- ABA-AA: A simple, reversible, and non-toxic anchor-away system for effective nuclear protein depletion.Cell reports methods · 2026Article
- SpotMAX: A generalist framework for multidimensional automatic spot detection and quantification.Science advances · 2026Article
- Glucose repression ofbioRxiv : the preprint server for biology · 2026Article
- SNF1/AMPK controls its own localization by phosphorylating its activating kinase Sak1.iScience · 2026Article
- Lipid droplet size profiling in yeast.Biology open · 2026Article
- Establishing MS2-MCP-based single-molecule RNA visualization in Schizosaccharomyces pombe.Journal of cell science · 2026Article
- Investigations into multiple fission yeast chromosome size determinants.Journal of cell science · 2026Article
- In the absence of mitochondrial fusion unequal segregation of mitochondria drives mtDNA loss.EMBO reports · 2026Article
- A Fkh1/2 binding site array in the WHI5 promoter drives sub-scaling transcription.Cell reports · 2026Article
- The role of cell growth rate on accumulation of the mitotic cyclin Cdc13 in fission yeast.bioRxiv : the preprint server for biology · 2026Article
- An automated workflow for fungal cell counting, cell size and data analysis: enhancing throughput and accuracy with the cell analysis and counting tool using ilastik software (caactus).BMC microbiology · 2026Article
- Development of Human Conjunctival Goblet Cell Segmentation Datasets to Improve Quantitation.Scientific data · 2026Article
- Synthetic data enables human-grade microtubule analysis with foundation models for segmentation.PLoS computational biology · 2026Article
- Peering Inside the Black Box: Explainable AI to Interpret Advanced Computer Vision Fungal Pathogen Prediction.Scientific reports · 2026Article
- Polo-like kinase Cdc5 orchestrates Cdk1 regulation via Swe1 and Mih1 during meiotic prophase I exit.Communications biology · 2026Article
- Single-cell aging trajectories reveal a dynamic coupling between nuclear size and proteasome concentration.iScience · 2026Article
- Establishing MS2-MCP-based single-molecule RNA visualization inbioRxiv : the preprint server for biology · 2026Article
- Cell enlargement drives aging-associated proteome remodeling and shortens replicative lifespan.bioRxiv : the preprint server for biology · 2026Article
- Love-thy-neighbor: Neural networks for tracking and lineage tracing in budding yeast.bioRxiv : the preprint server for biology · 2026Article
20 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The identification of cell borders ('segmentation') in microscopy images constitutes a bottleneck for large-scale experiments. For the model organism Saccharomyces cerevisiae, current segmentation methods face challenges when cells bud, crowd, or exhibit irregular features. We present a convolutional neural network (CNN) named YeaZ, the underlying training set of high-quality segmented yeast images (>10 000 cells) including mutants, stressed cells, and time courses, as well as a graphical user interface and a web application ( www.quantsysbio.com/data-and-software ) to efficiently employ, test, and expand the system. A key feature is a cell-cell boundary test which avoids the need for fluorescent markers. Our CNN is highly accurate, including for buds, and outperforms existing methods on benchmark images, indicating it transfers well to other conditions. To demonstrate how efficient large-scale image processing uncovers new biology, we analyze the geometries of ≈2200 wild-type and cyclin mutant cells and find that morphogenesis control occurs unexpectedly early and gradually.
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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.