On the number of genomic pacemakers: A geometric approach

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The universal pacemaker (UPM) model extends the classical molecular clock (MC) model, by allowing each gene, in addition to its individual intrinsic rate as in the MC, to accelerate or decelerate according to the universal pacemaker. Under UPM, the relative evolutionary rates of all genes remain nearly constant whereas the absolute rates can change arbitrarily. It was shown on several taxa groups spanning the entire tree of life that the UPM model describes the evolutionary process better than the MC model. In this work we provide a natural generalization to the UPM model that we denote multiple pacemakers (MPM). Under the MPM model every gene is still affected by a single pacemaker, however the number of pacemakers is not confined to one. Such a model induces a partition over the gene set where all the genes in one part are affected by the same pacemaker and task is to identify the pacemaker partition, or in other words, finding for each gene its associated pacemaker. We devise a novel heuristic procedure, relying on statistical and geometrical tools, to solve the problem and demonstrate by simulation that this approach can cope satisfactorily with considerable noise and realistic problem sizes. We applied this procedure to a set of over 2000 genes in 100 prokaryotes and demonstrated the significant existence of two pacemakers.

Original languageEnglish
Article number26
JournalAlgorithms for Molecular Biology
Issue number1
StatePublished - 31 Dec 2014

Bibliographical note

Funding Information:
Research was supported in part by the USA-Israel Binational Science Foundation. Part of this work was done while the author was visiting the National Center for Biotechnology Information (NCBI) at the National Institutes of Health (NIH), USA. We thank Eugene Koonin and Yuri Wolf for helpful discussions, in particular in interpretation of the biological significance of the resulted clustering of the real data in Section ‘Results on real data’.

Publisher Copyright:
© 2014 Snir.


  • Deming regression
  • Gap statistics
  • Genome evolution pacemaker
  • Molecular evolution
  • Partition distance

ASJC Scopus subject areas

  • Structural Biology
  • Molecular Biology
  • Computational Theory and Mathematics
  • Applied Mathematics


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  • Pacemaker partition identification

    Snir, S., 2014, Algorithms in Bioinformatics - 14th International Workshop, WABI 2014, Proceedings. Springer Verlag, p. 281-295 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8701 LNBI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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