| Literature DB >> 33402023 |
Alexander B Brummer1,2,3, Panagiotis Lymperopoulos4, Jocelyn Shen5, Elif Tekin1,3, Lisa P Bentley6, Vanessa Buzzard7, Andrew Gray8, Imma Oliveras9, Brian J Enquist8,10, Van M Savage1,2,3,10.
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.Entities:
Keywords: branching networks; machine learning; metabolic scaling; vascular biology
Mesh:
Year: 2021 PMID: 33402023 PMCID: PMC7879751 DOI: 10.1098/rsif.2020.0624
Source DB: PubMed Journal: J R Soc Interface ISSN: 1742-5662 Impact factor: 4.118