From: A new approach for prediction of tumor sensitivity to targeted drugs based on functional data
Avg Err | Drug | Error | Pred. Sens | Exp. Sens |
---|---|---|---|---|
0.036 | Veliparib (ABT-888) | 0.00 | 0.00 | 0.00 |
Selumetinib (AZD6244) | 0.00 | 0.00 | 0.00 | |
Bortezomib | 0.01 | 1.00 | 0.99 | |
Bosutinib (SKI-606) | 0.00 | 0.00 | 0.00 | |
Dasatinib | 0.03 | 0.83 | 0.85 | |
Erlotinib | 0.00 | 0.00 | 0.00 | |
Panobinostat (LBH-589) | 0.05 | 0.96 | 1.00 | |
Pazopanib (GW-786034) | 0.00 | 0.00 | 0.00 | |
PI-103 | 0.00 | 0.00 | 0.00 | |
Sorafenib | 0.00 | 0.00 | 0.00 | |
Vorinostat (SAHA) | 0.13 | 0.91 | 0.78 | |
Obatoclax (GX15-070) | 0.01 | 0.42 | 0.44 | |
Crizotinib (PF-2341066) | 0.04 | 0.66 | 0.69 | |
MK-2206 | 0.28 | 0.66 | 0.93 | |
Vismodegib (GDC-0449) | 0.00 | 0.00 | 0.00 | |
Alisertib (MLN8237) | 0.00 | 0.00 | 0.00 | |
SNS-032 (BMS-387032) | 0.00 | 1.00 | 1.00 | |
Carfilzomib | 0.01 | 0.99 | 1.00 | |
Imatinib | 0.00 | 0.00 | 0.00 | |
BIX 01294 | 0.23 | 1.00 | 0.89 | |
BMS-754807 | 0.00 | 1.00 | 1.00 | |
SJ-172550 | 0.00 | 0.00 | 0.00 | |
Barasertib (AZD1152-HQPA) | 0.00 | 0.00 | 0.00 | |
Ruxolitinib (INCB018424) | 0.00 | 0.00 | 0.00 | |
Cediranib (AZD2171) | 0.31 | 0.44 | 0.75 | |
Lapatinib | 0.00 | 0.00 | 0.00 | |
Sunitinib | 0.02 | 0.78 | 0.76 | |
Trichostatin A | 0.05 | 0.89 | 0.96 | |
Tozasertib (VX-680) | 0.00 | 1.00 | 1.00 | |
Enzastaurin | 0.00 | 0.00 | 0.00 | |
PD0332991 | 0.24 | 0.76 | 1.00 | |
Valproate | 0.00 | 0.00 | 0.00 | |
Resveratrol | 0.00 | 0.00 | 0.00 | |
Zibotentan (ZD4054) | 0.00 | 0.00 | 0.00 | |
SP600125 | 0.00 | 0.00 | 0.00 | |
Ponatinib (AP24534) | 0.00 | 0.00 | 0.00 | |
BIX 02188 | 0.03 | 0.92 | 0.89 | |
RO4929097 | 0.00 | 0.00 | 0.00 | |
Curcumin | 0.00 | 0.00 | 0.00 | |
Sodium butyrate | 0.00 | 0.00 | 0.00 | |
GANT61 | 0.00 | 0.00 | 0.00 | |
Aurothiomalate | 0.00 | 0.00 | 0.00 | |
(OSI-906) | 0.11 | 1.00 | 0.89 | |
Pelitinib (EKB-569) | 0.01 | 0.62 | 0.63 |