Drug Discovery
Drug discovery is the task of applying machine learning techniques to the identification and development of new drug candidates. Its goal is to predict compound activity through computational models, optimize the drug design process, enhance the efficiency and success rate of discovering potential therapeutic drugs, thereby accelerating the drug development cycle, reducing R&D costs, and improving innovation capabilities and treatment standards in the healthcare sector.
BACE
BACE (β-secretase enzyme)
BBBP
ProtoW-L2
BBBP (Blood-Brain Barrier Penetration)
BindingDB
AttentionSiteDTI
BindingDB IC50
DeepDTA
clintox
BiLSTM
DAVIS-DTA
DRD2
egfr-inh
Multi-input Neural network with Attention
ESOL (Estimated SOLubility)
FreeSolv (Free Solvation)
HIV dataset
GraphConv + dummy super node + focal loss
KIBA
SMT-DTA
Lipophilicity (logd74)
LIT-PCBA(ALDH1)
LIT-PCBA(ESR1_ant)
LIT-PCBA(KAT2A)
EGT+TGT-At-DP
LIT-PCBA(MAPK1)
MUV
TrimNet
PCBA
GraphConv + dummy super node
PDBbind
Ensemble locally constant networks
QED
HierG2G
QM9
PAMNet
SIDER
Ensemble locally constant networks
Tox21
elEmBERT-V1
ToxCast
ToxCast (Toxicity Forecaster)
GLAM