UPGMA and the normalized equidistant minimum evolution problem

Moulton, Vincent ORCID: https://orcid.org/0000-0001-9371-6435, Spillner, Andreas and Wu, Taoyang ORCID: https://orcid.org/0000-0002-2663-2001 (2018) UPGMA and the normalized equidistant minimum evolution problem. Theoretical Computer Science, 721. pp. 1-15. ISSN 0304-3975

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Abstract

UPGMA (Unweighted Pair Group Method with Arithmetic Mean) is a widely used clustering method. Here we show that UPGMA is a greedy heuristic for the normalized equidistant minimum evolution (NEME) problem, that is, finding a rooted tree that minimizes the minimum evolution score relative to the dissimilarity matrix among all rooted trees with the same leaf-set in which all leaves have the same distance to the root. We prove that the NEME problem is NP-hard. In addition, we present some heuristic and approximation algorithms for solving the NEME problem, including a polynomial time algorithm that yields a binary, rooted tree whose NEME score is within O(log2n) of the optimum.

Item Type:	Article
Uncontrolled Keywords:	upgma,minimum evolution,balanced minimum evolution,hierarchical clustering
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Computational Biology > Phylogenetics (former - to 2018) Faculty of Science > Research Groups > Computational Biology Faculty of Science > Research Groups > Computational Biology > Computational biology of RNA (former - to 2018) Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre Faculty of Science > Research Centres > Centre for Ecology, Evolution and Conservation Faculty of Science > Research Groups > Data Science and AI
Depositing User:	Pure Connector
Date Deposited:	25 Jan 2018 15:30
Last Modified:	17 Dec 2024 01:25
URI:	https://ueaeprints.uea.ac.uk/id/eprint/66076
DOI:	10.1016/j.tcs.2018.01.022

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