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Table 9 The added value of re-ranking models measured by cumulative observed model quality

From: Benchmarking consensus model quality assessment for protein fold recognition

  TM-score MaxSub GDT Combined
ModFOLD 0.42 0.42 0.47 0.44
ProQLG 0.27 0.32 0.33 0.31
PROQ* 0.23 0.34 0.30 0.29
MODCHECK 0.25 0.32 0.30 0.29
ProQMX -0.09 0.05 0.00 -0.01
3D-Jury -0.49 -0.61 -0.59 -0.56
ModSSEA -1.12 -1.06 -0.97 -1.05
Random -3.61 -3.56 -3.48 -3.55
  1. The mean difference in cumulative observed model quality scores if each MQAP method is used to re-rank the models from each individual fold recognition server. The results achieved from a random re-ranking of models from each server (random assignment of scores between 0 and 1) are also shown for comparison. * The official predicted MQAP scores for these methods were downloaded from CASP7 website; all other MQAP methods were run in house during the CASP7 experiment. † MQAP methods which rely on the comparison of multiple models or additional information from multiple servers; all other methods are capable of producing a single score for a single model.