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Table 3 Performance differences among algorithms for the homopolymers of length 64 and 32 in long runs.

From: An adaptive bin framework search method for a beta-sheet protein homopolymer model

Method Temperature set Length E avg ± sd E med E q 75 E q 25 E min p – value
our MC 1.25 32 -158.7 (± 1.9) -159 -159 -158 -161 0.0271*
our REMC linear 1.25 to 2.75 32 -159.6 (± 1.3) -160 -161 -158 -161 0.5471
our PHAT linear 1.3 to 2.75 32 -158.9 (± 1.4) -159 -159 -158 -161 0.0638
our BINMC T MC = 1.25, T bin = 6.521 32 -160.1 (± 0.9) -161 -161 -159 -161  
our MC 1.25 64 -372.2 (± 2.3) -372 -373 -371 -377 0.0005*
our REMC linear 1.25 to 2.75 64 -376.1 (± 3.5) -376 -378 -373 -382 0.0521
our PHAT linear 1.3 to 2.75 64 -374.1 (± 3.8) -374 -377 -371 -383 0.0120*
our BINMC T MC = 1.25, T bin = 6.521 64 -379.5 (± 3.3) -381 -382 -376 -389  
  1. Comparison of the energy levels reached for the homopolymers of length 64 and 32 by our implementations of MC, REMC (with the linear set of temperatures), PHAT, and the new BINMC algorithm in 10 independent runs of 10 CPU hours each on our 2.4 GHz reference machine. The p-values reported in the last column were determined using the Mann-Whitney U test to test the null hypothesis that the mean energies reached by the respective algorithm and BINMC (within the same CPU cut-off time) are identical [4]; p-values marked with an asterisk (*) correspond to cases in which the null hypothesis is rejected at a standard significance level of 0.05, and therefore indicate statistically significant performance differences.