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Table 4 Example characteristics of the first and second scenario designs

From: Cubic time algorithms of amalgamating gene trees and building evolutionary scenarios

  Artificial data Biological data
Scenario characteristics 1st design 2nd design 1st design 2nd design
Total cost / expectation 97443.4 151629.7 210917.0 535524.0
Total cost / expectation of gains 60.0 358.4 53448.0 77040.5
Total cost / expectation of losses 38024.0 56660.0 98376.0 187600.5
Total cost / expectation of duplications 26796.0 34324.6 38286.0 44639.6
Total cost / expectation of transfers 32563.4 60168.3 17887.0 223854.8
Total cost / expectation of the gain_big events 0.0 118.4 2920.0 2388.6
Running time <1m 2m 15m 41m
  1. Input tree data is the same as for Table 3. The tree S is obtained by the supertree building algorithm described in the paper. The degree of ramification k = 10. Individual event costs are as follows: c(dupl)=3, c(loss)=2, c(gain)=12, c(gain_big)=10, c(sleep)=20, c(tr_with)= 17.6, c(tr_without)=19.6. The running time is specified for parallel computations on a 16-CPUs platform. The cost in the second design and the expectation of the total event cost are defined in Table 3 and by formula (6), respectively.