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Table 4 Cumulative observed model quality scores for each MQAP (all models)

From: Benchmarking consensus model quality assessment for protein fold recognition

  TM-score MaxSub GDT Combined
3D-Jury 58.22 48.19 52.21 52.87
LEE* 55.17 45.66 49.59 50.14
Pcons* 54.47 45.81 49.20 49.82
ModFOLD 54.26 44.36 48.57 49.06
ModSSEA 53.73 43.24 47.65 48.21
PROQ* 51.20 42.82 45.99 46.67
PROQLG 49.32 41.62 44.63 45.19
PROQMX 46.93 39.04 42.23 42.73
MODCHECK 43.76 34.85 38.66 39.09
  1. The cumulative observed model quality scores of the top ranked models for each target (Σm) obtained by using each MQAP method to rank all models from all fold recognition servers.*The 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 based on a single model.