Before revision:  Here we classify diverse branching networks-mouse lung, human head and torso, angiosperm plants, and gymnosperm plants-by harnessing recent advances in medical imaging, algorithms and software for extracting vascular data, theory for resource-distribution networks, and machine-learning. Specifically, we apply standard machine-learning techniques to a variety of feature spaces. Our results show that our theoretically-informed feature spaces-especially those that determine blood flow rate-combined with Kernel Density Estimation are best at distinguishing networks.
After revision:  Here we classify 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 networks.