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Table 1 Performance evaluation (auROC and auPRC scores) of six different methods on the NN269 and DGSplicer Acceptor and Donor test sets. MC denotes prediction with a Markov Chain, EBN the method proposed in [36], and MC-SVM the SVM based method described in [32] (similar to [21]).

From: Accurate splice site prediction using support vector machines

  MC EBN MC-SVM LIK WD WDS
NN269       
   Acceptor       
   auROC 96.78 - 96.74 98.19 98.16 98.65
   auPRC 88.41 - 88.33 92.48 92.53 94.36
   Donor       
   auROC 98.18 - 97.64 98.04 98.50 98.13
   auPRC 92.42 - 89.57 92.65 92.86 92.47
DGSplicer       
   Acceptor       
   auROC 97.23 95.91* 95.35* - 97.50 97.28
   auPRC 30.59 - - - 32.08 28.58
   Donor       
   auROC 98.34 96.88* 95.08* - 97.84 97.47
   auPRC 41.72 - - - 39.72 35.59
  1. The remaining methods are based on SVMs using the locality improved kernel (LIK) [21], weighted degree kernel (WD) [28] and weighted degree kernel with shifts (WDS) [34]. The values marked with an asterisk were estimated from the figures provided in [32]. The values marked with † are from personal communication with the authors of [32].