2009
DOI: 10.1007/978-3-642-02777-2_3
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Efficiently Calculating Evolutionary Tree Measures Using SAT

Abstract: Abstract. We develop techniques to calculate important measures in evolutionary biology by encoding to CNF formulas and using powerful SAT solvers. Comparing evolutionary trees is a necessary step in tree reconstruction algorithms, locating recombination and lateral gene transfer, and in analyzing and visualizing sets of trees. We focus on two popular comparison measures for trees: the hybridization number and the rooted subtree-prune-and-regraft (rSPR) distance. Both have recently been shown to be NP-hard, an… Show more

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Cited by 17 publications
(16 citation statements)
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References 26 publications
(51 reference statements)
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“…There is an approximation algorithm of ratio 3 (Hein et al 1996), as well as an ILP algorithm for calculating an exact rooted SPR distance (Wu 2009). An exact rooted SPR distance is also determined by reducing it to CNF (Bonet and John 2009) and using existing SAT solvers.…”
Section: A Review Of Previous Resultsmentioning
confidence: 99%
“…There is an approximation algorithm of ratio 3 (Hein et al 1996), as well as an ILP algorithm for calculating an exact rooted SPR distance (Wu 2009). An exact rooted SPR distance is also determined by reducing it to CNF (Bonet and John 2009) and using existing SAT solvers.…”
Section: A Review Of Previous Resultsmentioning
confidence: 99%
“…Any subset of these pairs can be generated via the choice rule in line 4, permitting instances of edge/2 to hold without further preconditions. 1 For example, the atoms characterizing the directed graph in Figure 1(a) are edge (1,2), edge (1,3), edge (2,4), edge (3,2), edge (4,5), and edge (5,3).…”
Section: Directed Acyclic Graphsmentioning
confidence: 99%
“…For instance, Bayesian network structure learning, where directed acyclic graphs provide solution candidates, can be reduced to constraint optimization [15,28,16]. Constraint-based methods can also be used to infer phylogenetic trees [7,5], describing the evolution of living organisms, languages, and other evolving systems. Furthermore, chordal Markov network learning amounts to the task of optimizing maximum weight spanning trees induced by chordal graphs [14].…”
Section: Introductionmentioning
confidence: 99%
“…These formulas encode computing evolutionary tree measures into SAT [47]. The results of these instances are shown in Table 4.…”
Section: Bio-informaticsmentioning
confidence: 99%