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Table 3 Performance comparison CDUN with other approaches using CYC2008 as benchmark

From: An uncertain model-based approach for identifying dynamic protein complexes in uncertain protein-protein interaction networks

PPI Dataset Methods Precision Recall F-score Sn PPV Accuracy
DIP CDUN 0.6 0.551 0.575 0.431 0.641 0.526
CSO 0.497 0.623 0.553 0.538 0.631 0.582
Cluster ONE 0.337 0.441 0.382 0.378 0.696 0.513
COAN 0.41 0.597 0.486 0.445 0.529 0.483
COACH 0.307 0.602 0.406 0.544 0.456 0.498
CMC 0.485 0.428 0.455 0.306 0.643 0.443
HUNTER 0.852 0.119 0.208 0.164 0.644 0.325
MCODE 0.423 0.14 0.21 0.282 0.362 0.32
TransClust 0.13 0.674 0.218 0.622 0.725 0.672
SpecClust 0.122 0.331 0.179 0.548 0.529 0.538
MIPS CDUN 0.438 0.331 0.377 0.244 0.612 0.387
CSO 0.391 0.344 0.365 0.283 0.641 0.426
Cluster ONE 0.273 0.267 0.27 0.235 0.725 0.412
COAN 0.356 0.352 0.354 0.261 0.636 0.407
COACH 0.239 0.347 0.283 0.317 0.385 0.35
CMC 0.335 0.322 0.328 0.361 0.468 0.411
HUNTER 0.538 0.14 0.222 0.289 0.333 0.31
MCODE 0.365 0.153 0.215 0.189 0.572 0.329
TransClust 0.145 0.623 0.236 0.544 0.71 0.621
SpecClust 0.095 0.182 0.125 0.41 0.37 0.389
STRING CDUN 0.446 0.674 0.537 0.715 0.518 0.609
Cluster ONE 0.13 0.343 0.188 0.671 0.494 0.569
COACH 0.181 0.458 0.26 0.963 0.154 0.385
HUNTER 0.5 0.017 0.033 0.107 0.353 0.194
MCODE 0.079 0.131 0.099 0.681 0.257 0.418
TransClust 0.11 0.517 0.181 0.842 0.528 0.667
SpecClust 0.066 0.347 0.111 0.652 0.519 0.582
  1. The highest value of each dataset is in bold. Core_thresh is set 0.4 for CDUN