English

Branching principles of animal and plant networks identified by combining extensive data, machine learning, and modeling

Quantitative Methods 2021-01-07 v2

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.

Keywords

Cite

@article{arxiv.1903.04642,
  title  = {Branching principles of animal and plant networks identified by combining extensive data, machine learning, and modeling},
  author = {Alexander B Brummer and Panagiotis Lymperopoulos and Jocelyn Shen and Elif Tekin and Lisa P. Bentley and Vanessa Buzzard and Andrew Gray and Imma Oliveras and Brian J. Enquist and Van M. Savage},
  journal= {arXiv preprint arXiv:1903.04642},
  year   = {2021}
}

Comments

55 pages, 8 figures, 8 tables