ArticleApplications in plant sciences
SkelPy: A graphic user interface-based approach for skeletonizing fungal networks.
Article in Applications in plant sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Premise: Traditional methods to quantify mycelial growth rely on destructive sampling to quantify biomass. Moreover, these approaches limit continuous observation and require a sufficient mass to measure. Recent work examines hyphal network traits by reconstructing the hyphal network from spatial coordinates via images, providing information about branching patterns and spatial growth over time. Methods and Results: We developed SkelPy, a Python-based graphical user interface that skeletonizes images of hyphal networks and extracts biologically relevant structural parameters such as fractal dimension, a proxy for the complexity and branching structure of the hyphal network. Using a high-throughput pipeline, we imaged three isolates of Conclusions: SkelPy enables efficient, non-destructive, and scalable quantification of hyphal growth and complexity from time-resolved image datasets, providing a powerful and user-friendly tool for studying fungal network dynamics.
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