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Table 1 Therapy Classification

From: Host sequence motifs shared by HIV predict response to antiretroviral therapy

  Standard Datenum Incremental Reduction Bimodal Classification
  R NR Mean AUC R NR Mean AUC R NR Mean AUC
AZT 526 390 0.7750 581 335 0.8550 395 521 0.7802
AZT, IDV 182 148 0.7803 189 141 0.9281 144 186 0.9107
DDI 466 273 0.7572 503 236 0.8363 272 467 0.7648
DDI, NFV 249 130 0.7352 264 115 0.8004 175 204 0.6814
D4T 450 307 0.7654 482 275 0.8081 274 483 0.7683
D4T, NFV 266 153 0.7499 280 139 0.6664 181 238 0.6713
D4T, NFV 372 200 0.7377 391 181 0.8455 260 312 0.7613
D4T, DDI, NFV 234 115 0.7518 242 107 0.7764 173 176 0.6817
3TC 582 466 0.7721 654 394 0.9280 408 640 0.7788
3TC, IDV 187 151 0.7748 196 142 0.9030 144 194 0.8763
3TC, NFV 202 159 0.7535 242 119 0.8810 175 186 0.8606
3TC, AZT 509 379 0.7731 560 328 0.8439 391 497 0.7845
3TC, AZT, IDV 177 145 0.7849 184 138 0.8858 144 178 0.8815
DDI, EFV 248 121 0.7389 208 89 0.9312 192 177 0.6711
D4T, EFV 260 125 0.7406 285 100 0.8479 194 191 0.9887
D4T, DDI, EFV 233 107 0.7516 254 86 0.9446 188 152 0.7499
3TC, EFV 207 130 0.7313 245 100 0.9731 179 166 0.9497
All Therapies 1115 904 0.7644 1188 831 0.8351 700 1319 0.8402
  1. The overall statistics of the clinically annotated reverse transcriptase sequences from the Stanford HIV-1 Drug Resistance Database. The table shows breakdown of patients in each therapy regimen using the three different classification rules: Standard Datenum (SD), Incremental Reduction (IR), and Bimodal Classification (BM). R; responders, NR; non responders. The average AUC over 500 training/testing iterations indicate the success in differentiating responders from non responders using short linear sequence motifs as features in machine learning.