4.7 Article

On simulated annealing phase transitions in phylogeny reconstruction

Journal

MOLECULAR PHYLOGENETICS AND EVOLUTION
Volume 101, Issue -, Pages 46-55

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ympev.2016.05.001

Keywords

Phylogeny; Optimisation; Heuristic methods; Simulated annealing; Phase transition; Search landscape

Funding

  1. Genetics Society
  2. Biotechnology and Biological Sciences Research Council [BB/J01446X/1]
  3. Science and Technology Facilities Council [ST/M000435/1]
  4. University of St Andrews Undergraduate Research Assistants Internship Programme
  5. University of St Andrews Bioinformatics Unit - Wellcome Trust [097831/Z/11/Z]
  6. STFC [ST/M000435/1] Funding Source: UKRI
  7. Science and Technology Facilities Council [ST/M000435/1] Funding Source: researchfish

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Phylogeny reconstruction with global criteria is NP-complete or NP-hard, hence in general requires a heuristic search. We investigate the powerful, physically inspired, general-purpose heuristic simulated annealing, applied to phylogeny reconstruction. Simulated annealing mimics the physical process of annealing, where a liquid is gently cooled to form a crystal. During the search, periods of elevated specific heat occur, analogous to physical phase transitions. These simulated annealing phase transitions play a crucial role in the outcome of the search. Nevertheless, they have received comparably little attention, for phylogeny or other optimisation problems. We analyse simulated annealing phase transitions during searches for the optimal phylogenetic tree for 34 real-world multiple alignments. In the same way in which melting temperatures differ between materials, we observe distinct specific heat profiles for each input file. We propose this reflects differences in the search landscape and can serve as a measure for problem difficulty and for suitability of the algorithm's parameters. We discuss application in algorithmic optimisation and as a diagnostic to assess parameterisation before computationally costly, large phylogeny reconstructions are launched. Whilst the focus here lies on phylogeny reconstruction under maximum parsimony, it is plausible that our results are more widely applicable to optimisation procedures in science and industry. (C) 2016 The Authors. Published by Elsevier Inc.

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