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. 2009 Jul 31;9:51. doi: 10.1186/1472-6807-9-51

Table 3.

Evaluation of the Real-SPINE and NetSurfP method on subsets of residues from the CB511 dataset predicted with high reliability.

Real-SPINE NetSurfP
%Top N RSA ASA P-RSA M-RSA RSA ASA P-RSA M-RSA

10 8372 0.73 0.74 0.16 0.18 0.77 0.79 0.35 0.35
20 16745 0.73 0.74 0.16 0.18 0.79 0.79 0.31 0.31
25 20931 0.73 0.74 0.17 0.19 0.79 0.79 0.30 0.30
50 41863 0.72 0.74 0.18 0.20 0.77 0.77 0.28 0.28
75 62795 0.71 0.73 0.22 0.24 0.74 0.75 0.28 0.28
80 66981 0.71 0.73 0.23 0.25 0.73 0.74 0.28 0.28
90 75354 0.70 0.73 0.25 0.27 0.72 0.73 0.28 0.28
100 83727 0.70 0.73 0.27 0.29 0.70 0.72 0.29 0.29

%Top and N give the percentage and number of residues selected. RSA and ASA give the Pearson's correlation between predicted and target for relative and absolute surface areas, respectively. P-RSA, and M-RSA give the mean predicted and mean measured RSA values, respectively, on the selected subset of residues.