Development· 2026Q1
Mastodon: the command center for large-scale lineage-tracing microscopy datasets
- 4citations
- Q1SCImago
- 2026year
Short summary
Mastodon is a new, scalable software platform designed to overcome computational challenges in analyzing cell lineages from large microscopy datasets, enabling manual, semi-automated, and automated cell tracking.
AI-generated from the title and abstract; the full text is not read.
Key points
- Mastodon is a software platform for cell tracking in large microscopy datasets.
- It supports manual, semi-automated, and automated tracking methods.
- A graph model allows for responsive performance with millions of annotations.
- Mastodon integrates with Fiji and Blender for visualization and 3D analysis.
- The platform is shown to accelerate biological insights in developmental studies.
AI-generated from the title and abstract; the full text is not read.
Abstract
Understanding development in living organisms requires following the divisions, movements, and fates of cells. While advances in microscopy have enabled whole-embryo imaging at the cellular level, extracting and analyzing cell lineages from these massive datasets remains a significant computational challenge. We present Mastodon, a scalable, extensible software platform for manual, semi-automated, and automated cell tracking in large images. A purpose-built graph model supports responsive performance for datasets with millions of annotations, making Mastodon a scalable platform for cell lineage analysis. Built as a Fiji plugin, Mastodon enables interactive visualization, editing, and analysis of complex lineage trees, seamlessly integrated with the raw image data. Comprehension of cell lineages in complex three-dimensional geometries is facilitated by interoperability with the powerful open-source render engine Blender. In three distinct developmental contexts, we demonstrate how Mastodon will accelerate biological insights by providing user-friendly navigation and explorative analysis in complex lineage datasets.
The authors' abstract, as published at the source. Development, 2026 · DOI ↗
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BiophysicsBiochemistry, Genetics and Molecular Biology