DRPMKB knowledgebase

Model Information

Model name statistics help organize and summarize research in drug repositioning prediction. They provide a framework for researchers to compare model characteristics and advantages. Many models use single-letter names, complicating research. This page highlights model names in DRPMKB1.0, offering a foundation for future research and facilitating access to key information.

DATA INFORMATION
Category	Alphabetical sorting	All model name
Model Name	A-E	AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) / Affinity2Vec / ANMF / ANTENNA / Anti-Biofilm / Anti-Dengue / AOPEDF (Arbitrary-Order Proximity Embedded Deep Forest) / AttentionSiteDTI / BANDIT / BEHOR / BG-DTI / BGMSDDA / BiFusion (Bipartite graph convolution network) / BIMC / BindingSite-AugmentedDTA / BNNR (Bounded Nuclear Norm Regularization) / BRDTI / CATNIP / CauseNet / CBPred / CMLDR / CSConv2d / CTST / DAMT-Model / DDAGDL / DDAPRED / DDIPred / DDR / DDTE / DEDTI-IEDTI / deepDR / DeepFusion / DeepLPI / DGCL (Dynamic hyperGraph Contrastive Learning) / DGDTA / DisDrugPred / DLDTI / DNDTI / DOTA (Drug repositioning approach using Optimal Transport for Alzheimer's disease) / DR2DI / DRAGNN / DRDA / DRDSA (Drug Repositioning Deep Sparse Autoencoder) / DREAMwalk / DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) / DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) / DRONet / DrPOCS (projection onto convex sets) / DRRS (Drug Repositioning Recommendation System) / DrugRep-HeSiaGraph / DrugRep-KG / DRWBNCF / DT2Vec / DT2Vec+ / DTI-End-to-End-DL / DTI-GTN / DTI-HeNE (DTI based on Heterogeneous Network Embedding) / DTI-HETA / DTI-MLCD / DTINet / DTIP_MDHN / dtipred / DTI-SNNFRA / DTSEA (Drug Target Set Enrichment Analysis) / DVA (Drug Virus Association) / EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks)
	F-J	GANDTI / GCAN (GRU-Cooperation-Attention-Network) / GCMM (Graph convolution network based on a multimodal attention mechanism) / GCNMK / GDRnet / GEFA (Graph Early Fusion Affinity) / geNnius (Graph Embedding Neural Network Interaction Uncovering System) / GIFDTI / GIPAE (Gaussian interaction profile kernel and autoencoder) / GLGMPNN / GraphDTA / GraphPK (Graph-based Prior Knowledge) / GraphRepur / HAMN (Hybrid Attentional Memory Network) / Heter-LP / HINGRL / HMLKGAT / HNet-DNN / ICAN (Interpretable Cross-Attention Network) / IDDI-DNN / iDrug / IMCHGAN (Inductive Matrix Completion with Heterogeneous Graph Attention Network) / IntegratedSim / IRNMF (Indicator Regularized non-negative Matrix Factorization)
	K-O	KGE_NFM / KUALA (Kinase drUgs mAchine Learning frAmework) / LASSO / LBD / LMFDA / LRSSL (Laplacian regularized sparse subspace learning) / LUNAR / MBiRW / MccDTI / MCM / MdDTI / MDTips / MGATRx / MHADTI (Multiview heterogeneous information network embedding with Hierarchical Attention mechanisms to discover potential Drug–Target Interaction) / MHGNN (Metapath-aggregated Heterogeneous Graph Neural Network) / MHSADTI / MLAN (Multi-Level Attention Network) / MLMC / MNBDR (Module Network Based Drug Repositioning) LINC1000,Cmap / MOVE / MPTN / MSBMF / MSDF-CNN / MSGNN-DTA / MTLDR (Multi-task learning framework for drug repurposing) / MULGA (Multi-view Learning and Graph Autoencoder framework) / MultiDTI (Multi-modal DTI) / NA / NEDD / NEDNBI / NeoDTI (NEural integration of neighbOr information for DTI prediction) / NerLTR-DTA / NetPro / NMFDR (Neural Metric Factorization model for computational Drug Repositioning) / NMF-DR (Non-negative Matrix Factorization Drug Repurposing) / NMTF (Non-negative Matrix Tri-Factorization) / NTD-DR / NTSIM (Network Topological Similarity-based Inference Method) / OCSVM (One-class Support Vector Machine) / OMC
	P-T	PD-MRW / PhenoPredict / PIMD / PPAEDTI / PREDICT (PREdicting Drug IndiCaTions) / PreDR (Predict Drug Repositioning) / PSGCN (Partner-specific drug repositioning approach based on graph convolutional network) / PUDTI / PUON / RBM model / REDDA (Relations-Enhanced Drug-Disease Association prediction) / REMAP / RepCOOL / RLSDR (Regularized Least Square for Drug Repositioning) / Ro-DNILMF / RWHNDR (Random Walk on a Heterogeneous Network for Drug Repositioning) / SATS / SAveRUNNER (Searching off-lAbel dRUg aNd NEtwoRk) / SDTNBI (Substructure–drug–target network-based inference) / SHGCL-DTI / SiSGC (Simplifying Graph Convolution) / SKCNN / SNF-NN (Similarity network fusion and neural networks) / SPLCMF (Self-paced learning with collaborative matrix factorization) / SPLNMTF (Self-Paced Non-negative Matrix Tri-Factorization) / springD²A / SSGC (Semi-Supervised Graph Cut) / SSLDR / TeM-DTBA (Time-efficient Multimodal Drug Target Binding Affinity) / TL_HGBI (Triple Layer Heterogeneous Graph Based Inference) / TNA-DR (Tail-Node Augmentation for Drug Repositioning) / TP-NRWRH / TransRGNN / TransVAE-DTA (Transformer and Variational Autoencoder network for Drug-Target binding Affinity) / TS-SVD
	U-Z	VGAEDTI / WES / WMAGT