BioMed Research International / 2013 / Article / Tab 4 / Research Article
Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction Table 4 The effect of using HP energy model within a macro-mutation operator. The bold-faced values indicate the winner. The lower the energy value, the better the performance.
Protein details Best of 50 runs Average of 50 runs Rel. Imp. RI Seq Size H HP BM BD BH HP(
) BM(
) BD BH(
) HP BM 4RXN 54 27 −135.43 −167.90 −162.81 −166.88 −124.32 −159.92 −155.64 −162.72 30.89% 1.75% 1ENH 54 19 −134.97 −155.49 −150.07 −153.79 −125.52 −147.42 −144.47 −151.65 20.82% 2.87% 4PTI 58 32 −171.28 −213.05 −202.33 −210.29 −156.43 −201.12 −196.86 −204.56 30.77% 1.71% 2IGD 61 25 −153.00 −181.93 −177.19 −183.18 −140.59 −173.62 −170.79 −176.83 25.78% 1.85% 1YPA 64 38 −232.94 −255.40 −251.78 −256.95 −220.35 −247.17 −242.89 −253.09 14.86% 2.4% 1R69 69 30 −181.44 −212.35 −213.34 −216.37 −171.79 −203.26 −199.65 −208.79 21.54% 2.72% 1CTF 74 42 −202.06 −225.59 −225.37 −233.51 −190.31 −217.02 −212.05 −225.42 18.45% 3.87% 3MX7 90 44 −295.16 −333.74 −323.67 −340.05 −281.99 −317.11 −311.92 −325.45 15.41% 2.63% 3NBM 108 56 −380.20 −426.35 −424.10 −436.76 −364.99 −406.11 −400.17 −419.25 14.87% 3.24% 3MQO 120 68 −443.84 −472.15 −464.09 −486.05 −420.38 −452.32 −443.08 −472.78 12.46% 4.52% 3MRO 142 63 −420.65 −445.19 −444.99 −479.36 −401.32 −420.86 −421.61 −447.77 11.57% 6.39% 3PNX 160 84 −576.77 −584.17 −576.09 −615.82 −549.03 −542.68 −535.40 −592.25 7.87% 9.13%
