Abstract / Description of output
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. While 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.
Original language | English |
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Pages (from-to) | 46–55 |
Journal | Molecular phylogenetics and evolution |
Volume | 101 |
Early online date | 2 May 2016 |
DOIs | |
Publication status | Published - Aug 2016 |
Keywords / Materials (for Non-textual outputs)
- phylogeny
- optimisation
- heuristic methods
- simulated annealing
- phase transition
- search landscape
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Supplementary text and multiple sequence alignments from 'On simulated annealing phase transitions in phylogeny reconstruction'
Strobl, M. A. (Creator) & Barker, D. (Creator), Edinburgh DataShare, 4 Oct 2022
DOI: 10.7488/ds/3768, https://doi.org/10.1016/j.ympev.2016.05.001
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