On the complexity of computing evolutionary trees

Leszek Gasieniec, Jesper Jansson, Andrzej Lingas, Anna Östlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In this paper we study a few important tree optimization problems with applications to computational biology. These problems ask for trees that are consistent with an as large part, of the given data as possible. We show that the maximum homeomorphic agreement subtree problem cannot be approximated within a factor of Nε, where N is the input size, for any 0 ≤ ε < 1/18 in polynomial time unless P=NP, even if all the given trees are of height 2. On the other hand, we present an O(N log N)-time heuristic for the restriction of this problem to instances with O(1) trees of height O(1) yielding solutions within a constant factor of the optimum. We prove that the maximum inferred consensus tree problem is NP-complete, and we provide a simple fast heuristic for it yielding solutions within one third of the optimum. We also present a more specialized polynomial-time heuristic for the maximum inferred local consensus tree problem.

Original languageEnglish (US)
Title of host publicationComputing and Combinatorics - 3rd Annual International Conference COCOON 1997, Proceedings
EditorsTao Jiang, D.T. Lee
PublisherSpringer Verlag
Pages134-145
Number of pages12
ISBN (Print)354063357X, 9783540633570
DOIs
StatePublished - 1997
Externally publishedYes
Event3rd Annual International Computing and Combinatorics Conference, COCOON 1997 - Shanghai, China
Duration: Aug 20 1997Aug 22 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1276
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd Annual International Computing and Combinatorics Conference, COCOON 1997
Country/TerritoryChina
CityShanghai
Period8/20/978/22/97

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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