NDLI: Cophenetic Median Trees Under the Manhattan Distance

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Cophenetic Median Trees Under the Manhattan Distance

Content Provider	ACM Digital Library
Author	Markin, Alexey Eulenstein, Oliver
Abstract	Computing median trees from gene trees using path-difference metrics has provided several credible species tree estimates. Similar to these metrics is the cophenetic family of metrics that originates from a dendrogram comparison metric introduced more than 50 years ago. Despite the tradition and appeal of the cophenetic metrics, the problem of computing median trees under this family of metrics has not been analyzed. Like other standard median tree problems relevant in practice, as we show here, this problem is also NP-hard. NP-hard median tree problems have been successfully addressed by local search heuristics that are solving thousands of instances of a corresponding local search problem. For the local search problem under a cophenetic metric the best known (naive) algorithm has a time complexity that is typically prohibitive for effective heuristic searches. Focusing on the Manhattan norm (Manhattan cophenetic metric), we describe an efficient algorithm for this problem that improves on the naive solution by a factor of n, where n is the size of the input trees. We demonstrate the performance of our local search algorithm in a comparative study using published empirical data sets.
Starting Page	194
Ending Page	202
Page Count	9
File Format	PDF
ISBN	9781450347228
DOI	10.1145/3107411.3107443
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-08-20
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Local search Cophenetic distance Median trees Phylogenetics Sp
Content Type	Text
Resource Type	Article

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