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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
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Related Experiment Video

Updated: Sep 20, 2025

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data
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Two metrics on rooted unordered trees with labels.

Yue Wang1,2

  • 1Department of Computational Medicine, University of California, Los Angeles, USA. yuew@g.ucla.edu.

Algorithms for Molecular Biology : AMB
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New metrics for comparing developmental trees offer advantages over existing methods. These metrics are efficient to compute and applicable beyond developmental biology, particularly in molecular biology.

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LabelMetricSemimetricUnordered tree

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Area of Science:

  • Computational Biology
  • Developmental Biology
  • Tree Metrics

Background:

  • Early zygote development can be modeled using developmental trees.
  • Comparing developmental trees across species requires defining tree distances.
  • Developmental trees can be represented as rooted trees with ordered or unordered, labeled or unlabeled vertices.

Purpose of the Study:

  • To define novel metrics for comparing developmental trees.
  • To address limitations of existing methods for tree comparison.
  • To develop efficient algorithms for computing distances between developmental trees.

Main Methods:

  • Defined two metrics: best-match and left-regular, on the space of rooted unordered trees.
  • Defined a semimetric (a variant of the best-match metric) on the space of rooted labeled trees.
  • Analyzed the computational complexity of the proposed metrics.

Main Results:

  • The best-match and left-regular metrics show advantages over existing methods for unordered trees.
  • A novel semimetric was defined for ordered or unordered labeled trees.
  • Efficient algorithms were developed with polynomial time complexity for computing distances.

Conclusions:

  • Novel metrics and a semimetric are defined for rooted labeled trees with unordered vertices.
  • These metrics offer computational advantages and broader applicability.
  • The defined metrics can be applied to various tree structures, especially in molecular biology.