Abstract
Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi and animals. By combining machine-learning techniques with new theory that relates vascular form to metabolic function, we enable novel classification of diverse branching networks - mouse lung, human head and torso, angiosperm and gymnosperm plants. We find that ratios of limb radii - which dictate essential biologic functions related to resource transport and supply - are best at distinguishing branching networks. We also show how variation in vascular and branching geometry persists despite observing a convergent relationship across organisms for how metabolic rate depends on body mass.
Original language | English (US) |
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Article number | 20200624 |
Journal | Journal of the Royal Society Interface |
Volume | 18 |
Issue number | 174 |
DOIs | |
State | Published - Jan 2021 |
Keywords
- branching networks
- machine learning
- metabolic scaling
- vascular biology
ASJC Scopus subject areas
- Biotechnology
- Biophysics
- Bioengineering
- Biomaterials
- Biochemistry
- Biomedical Engineering