Gillette Todd A, Grefenstette John J
Center for Neural Informatics, Structure, & Plasticity and Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA 22030, USA.
Neuroinformatics. 2009 Sep;7(3):191-4. doi: 10.1007/s12021-009-9053-2. Epub 2009 Jul 28.
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.
受限树编辑距离提供了一种计算上可行的方法，可直接比较形态，而无需先提取其他度量的分布。回顾了Heumann和Wittum将受限树编辑距离应用于海马树突的情况，并在其他应用和潜在未来用途的背景下进行了考虑。该方法已用于神经肌肉投射轴突以比较拓扑结构，也用于树木以比较具有特定参数集的植物结构，这些参数集可能为未来比较树突形态的工作提供参考。虽然在小规模上显然是可行的，但运行时间的测试和外推引发了关于受限树编辑距离在大规模数据挖掘项目中的实用性的问题。然而，其他更高效的算法可能会将其用作直接形态比较的黄金标准。
