title: On comparing neuronal morphologies with the constrained tree-edit-distance.
abstract: The constrained tree-edit-distance provides a computationally practical method for comparing morphologies directly without first extracting distributions of other metrics. The application of the constrained tree-edit-distance to hippocampal dendrites by Heumann and Wittum is reviewed and considered in the context of other applications and potential future uses. The method has been used on neuromuscular projection axons for comparisons of topology as well as on trees for comparing plant architectures with particular parameter sets that may inform future efforts in comparing dendritic morphologies. While clearly practical on a small scale, testing and extrapolation of run-times raise questions as to the practicality of the constrained tree-edit-distance for large-scale data mining projects. However, other more efficient algorithms may make use of it as a gold standard for direct morphological comparison.
authors.affiliation: Center for Neural Informatics, Structure, & Plasticity and Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA 22030, USA. tgillett@gmu.edu
authors.forename: Todd A
authors.initials: TA
authors.lastname: Gillette
authors.forename: John J
authors.initials: JJ
authors.lastname: Grefenstette
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D019992:Databases as Topic / Q000458:organization & administration*; D003712:Dendrites / Q000502:physiology / Q000648:ultrastructure; D006801:Humans; D019044:Image Cytometry / Q000379:methods*; D008432:Mathematical Computing; D009474:Neurons / Q000166:cytology* / Q000502:physiology; D012984:Software; D012986:Software Validation