Full Identification of a Growing and Branching Network's Spatio-Temporal Structures
Thibault Chassereau, Florence Chapeland-Leclerc, Eric Herbert

TL;DR
This paper introduces a comprehensive method for reconstructing and analyzing the spatio-temporal growth of branching networks, demonstrated on a filamentous fungus, enabling detailed insights into growth dynamics and branch differentiation.
Contribution
A novel global network reconstruction method that labels and tracks each connection, distinguishes branch types, and eliminates overlaps for accurate growth analysis.
Findings
Outer ring mainly composed of apical branches
Densification driven by lateral branches
Reconstruction of growth timing without latency phase
Abstract
Experimentally monitoring the kinematics of branching network growth is a tricky task, given the complexity of the structures generated in three dimensions. One option is to drive the network in such a way as to obtain two-dimensional growth, enabling a collection of independent images to be obtained. The density of the network generates ambiguous structures, such as overlaps and meetings, which hinder the reconstruction of the chronology of connections. In this paper, we propose a general method for global network reconstruction. Each network connection is defined by a unique label, enabling it to be tracked in time and space. In this work, we distinguish between lateral and apical branches on the one hand, and extremities on the other. Finally, we reconstruct the network after identifying and eliminating overlaps. This method is then applied to the model filamentous fungus Podospora…
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Taxonomy
TopicsData Management and Algorithms · Advanced Database Systems and Queries · Neural Networks and Applications
