Estimating the deviation from a molecular clock

Luay Nakhleh, Usman Roshan, Lisa Vawter, Tandy Warnow

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

4 Scopus citations


We address the problem of estimating the degree to which the evolutionary history of a set of molecular sequences violates a strong molecular clock hypothesis.We quantify this deviation formally, by defining the “stretch” of a model tree with respect to the underlying ultrametric tree (indicated by time). We then define the “minimum stretch” of a dataset for a tree and show how this can be computed optimally in polynomial time. We also present a polynomial-time algorithm for computing a lower bound on the stretch of a given dataset for any tree. We then explore the performance of standard techniques in systematics for estimating the deviation of a dataset from a molecular clock. We show that standard methods, whether based upon maximum parsimony or maximum likelihood, can return infeasible values (i.e. values for the stretch which cannot be realized on a tree), and often under-estimate the true stretch. This suggests that current approximations of the degree to which data sets deviate from a molecular clock may significantly underestimate these deviations. We conclude with some suggestions for further research.

Original languageEnglish (US)
Title of host publicationAlgorithms in Bioinformatics - 2nd International Workshop,WABI 2002, Proceedings
EditorsRoderic Guigo, Dan Gusfield
PublisherSpringer Verlag
Number of pages13
ISBN (Print)3540442111, 9783540442110
StatePublished - 2002
Externally publishedYes
Event2nd International Workshop on Algorithms in Bioinformatics, WABI 2002 - Rome, Italy
Duration: Sep 17 2002Sep 21 2002

Publication series

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


Other2nd International Workshop on Algorithms in Bioinformatics, WABI 2002

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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