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Updated: Jun 8, 2026
08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
Large-scale analysis of phylogenetic search behavior.
Hyun Jung Park1, Seung-Jin Sul, Tiffani L Williams
1Department of Computer Science, Rice University, Houston, TX, USA. hp6@cs.rice.edu
Advances in Experimental Medicine and Biology
|September 25, 2010
Summary
Understanding phylogenetic heuristic search is key for accurate evolutionary relationship depictions. This study reveals that improving local optima also enhances surrounding tree neighborhoods, aiding heuristic design.
Area of Science:
- Evolutionary Biology
- Computational Biology
- Bioinformatics
Background:
- Phylogenetic analysis is crucial across biology, from human population origins to disease transmission patterns.
- Accurate phylogenetic trees depend on effective heuristics, yet their behavior in tree space is under-quantified.
Purpose of the Study:
- To quantitatively analyze the local search behavior of phylogenetic heuristics.
- To provide insights for designing improved heuristics for more accurate evolutionary relationship reconstructions.
Main Methods:
- Examined local search behavior for maximum parsimony on three biological datasets (44, 60, and 174 taxa).
- Analyzed all trees generated during the search process to understand neighborhood dynamics.
Main Results:
- As search algorithms approach local optima, neighboring trees also show improvement.
- The search process demonstrates robustness when incorporating a small number of randomly selected neighbors.
Conclusions:
- Exploring diverse tree collections offers valuable insights into local search algorithm behavior.
- Findings can guide the development of more effective phylogenetic heuristic algorithms.
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