Graph Neural Networks in Modern AI-aided Drug Discovery | Paper Citation Record

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This paper cites Modelling compound cytotoxicity using conformal prediction and PubChem HTS data.

Graph Neural Networks in Modern AI-aided Drug Discovery Modelling compound cytotoxicity using conformal prediction and PubChem HTS data

Reference 1

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This paper cites ParaVS: A Simple, Fast, Efficient and Flexible Graph Neural Network Framework for Structure-Based Virtual Screening.

Graph Neural Networks in Modern AI-aided Drug Discovery ParaVS: A Simple, Fast, Efficient and Flexible Graph Neural Network Framework for Structure-Based Virtual Screening

Reference 2

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This paper cites (375) Evans, R.; O’Neill, M.; Pritzel, A.; Antropova, N.; Senior, A.; Green, T.; Ž ídek, A.; Bates, R.; Blackwell, S.; Yim, J.

Graph Neural Networks in Modern AI-aided Drug Discovery (375) Evans, R.; O’Neill, M.; Pritzel, A.; Antropova, N.; Senior, A.; Green, T.; Ž ídek, A.; Bates, R.; Blackwell, S.; Yim, J

Reference 3

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This paper cites Why should i trust you?.

Graph Neural Networks in Modern AI-aided Drug Discovery Why should i trust you?

Reference 4

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Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 15

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This paper cites Tankbind: Trigonometry-aware neural networks for drug-protein binding structure prediction.

Graph Neural Networks in Modern AI-aided Drug Discovery Tankbind: Trigonometry-aware neural networks for drug-protein binding structure prediction

Reference 23

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This paper cites DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking.

Graph Neural Networks in Modern AI-aided Drug Discovery DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

Reference 24

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This paper cites Algorithm for reaction classification.

Graph Neural Networks in Modern AI-aided Drug Discovery Algorithm for reaction classification

Reference 25

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Observation 8969de5d-8594-4dd8-92f7-5191e2dc99cc · outbound

This paper cites Fabind: Fast and accurate protein-ligand binding.

Graph Neural Networks in Modern AI-aided Drug Discovery Fabind: Fast and accurate protein-ligand binding

Reference 26

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This paper cites FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose Generation.

Graph Neural Networks in Modern AI-aided Drug Discovery FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose Generation

Reference 27

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This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Graph Neural Networks in Modern AI-aided Drug Discovery Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 30

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This paper cites K.; Berman, H.

Graph Neural Networks in Modern AI-aided Drug Discovery K.; Berman, H

Reference 31

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This paper cites Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking.

Graph Neural Networks in Modern AI-aided Drug Discovery Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking

Reference 32

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This paper cites P.; Nguyen, T.; Le, T.

Graph Neural Networks in Modern AI-aided Drug Discovery P.; Nguyen, T.; Le, T

Reference 34

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This paper cites Uncertainty quantification over graph with conformalized graph neural networks.

Graph Neural Networks in Modern AI-aided Drug Discovery Uncertainty quantification over graph with conformalized graph neural networks

Reference 36

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Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 37

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This paper cites R.; Baumgartner, M.

Graph Neural Networks in Modern AI-aided Drug Discovery R.; Baumgartner, M

Reference 38

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This paper cites Graph normalizing flows.

Graph Neural Networks in Modern AI-aided Drug Discovery Graph normalizing flows

Reference 39

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This paper cites GraphNVP: An Invertible Flow Model for Generating Molecular Graphs.

Graph Neural Networks in Modern AI-aided Drug Discovery GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

Reference 40

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This paper cites MolGAN: An implicit generative model for small molecular graphs.

Graph Neural Networks in Modern AI-aided Drug Discovery MolGAN: An implicit generative model for small molecular graphs

Reference 41

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This paper cites DiGress: Discrete Denoising diffusion for graph generation.

Graph Neural Networks in Modern AI-aided Drug Discovery DiGress: Discrete Denoising diffusion for graph generation

Reference 42

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This paper cites MolecularRNN: Generating realistic molecular graphs with optimized properties.

Graph Neural Networks in Modern AI-aided Drug Discovery MolecularRNN: Generating realistic molecular graphs with optimized properties

Reference 43

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This paper cites GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation.

Graph Neural Networks in Modern AI-aided Drug Discovery GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

Reference 44

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This paper cites Categorical Normalizing Flows via Continuous Transformations.

Graph Neural Networks in Modern AI-aided Drug Discovery Categorical Normalizing Flows via Continuous Transformations

Reference 45

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This paper cites Graphdf: A discrete flow model for molecular graph generation.

Graph Neural Networks in Modern AI-aided Drug Discovery Graphdf: A discrete flow model for molecular graph generation

Reference 46

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This paper cites -S.; Shin, K.; Kang, S.

Graph Neural Networks in Modern AI-aided Drug Discovery -S.; Shin, K.; Kang, S

Reference 47

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This paper cites MARS: Markov Molecular Sampling for Multi-objective Drug Discovery.

Graph Neural Networks in Modern AI-aided Drug Discovery MARS: Markov Molecular Sampling for Multi-objective Drug Discovery

Reference 48

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This paper cites J.; Segler, M.; Hernández -Lobato, J.

Graph Neural Networks in Modern AI-aided Drug Discovery J.; Segler, M.; Hernández -Lobato, J

Reference 49

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This paper cites De Novo Molecular Generation via Connection-aware Motif Mining.

Graph Neural Networks in Modern AI-aided Drug Discovery De Novo Molecular Generation via Connection-aware Motif Mining

Reference 50

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This paper cites A Generative Model for Molecular Distance Geometry.

Graph Neural Networks in Modern AI-aided Drug Discovery A Generative Model for Molecular Distance Geometry

Reference 51

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Graph Neural Networks in Modern AI-aided Drug Discovery Learning Neural Generative Dynamics for Molecular Conformation Generation

Reference 52

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This paper cites Direct Molecular Conformation Generation.

Graph Neural Networks in Modern AI-aided Drug Discovery Direct Molecular Conformation Generation

Reference 53

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This paper cites GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation.

Graph Neural Networks in Modern AI-aided Drug Discovery GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation

Reference 54

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Graph Neural Networks in Modern AI-aided Drug Discovery Torsional Diffusion for Molecular Conformer Generation

Reference 55

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Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 56

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Graph Neural Networks in Modern AI-aided Drug Discovery E (n) equivariant normalizing flows

Reference 57

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Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 58

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Graph Neural Networks in Modern AI-aided Drug Discovery Symmetry -adapted generation of 3d point sets for the targeted discovery of molecules

Reference 59

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Graph Neural Networks in Modern AI-aided Drug Discovery W.; Gastegger, M.; Hessmann, S

Reference 60

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This paper cites A 3D generative model for structure -based drug design.

Graph Neural Networks in Modern AI-aided Drug Discovery A 3D generative model for structure -based drug design

Reference 62

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This paper cites Structure-based Drug Design with Equivariant Diffusion Models.

Graph Neural Networks in Modern AI-aided Drug Discovery Structure-based Drug Design with Equivariant Diffusion Models

Reference 64

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This paper cites DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding.

Graph Neural Networks in Modern AI-aided Drug Discovery DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding

Reference 65

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Graph Neural Networks in Modern AI-aided Drug Discovery 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction

Reference 66

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This paper cites DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design.

Graph Neural Networks in Modern AI-aided Drug Discovery DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design

Reference 67

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Graph Neural Networks in Modern AI-aided Drug Discovery Automated exploration of the low -energy chemical space with fast quantum chemical methods

Reference 68

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This paper cites P.; Plowright, A.

Graph Neural Networks in Modern AI-aided Drug Discovery P.; Plowright, A

Reference 70

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Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 71

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This paper cites Delete: Deep Lead Optimization Enveloped in Protein Pocket through Unified Deleting Strategies and a Structure-aware Network.

Graph Neural Networks in Modern AI-aided Drug Discovery Delete: Deep Lead Optimization Enveloped in Protein Pocket through Unified Deleting Strategies and a Structure-aware Network

Reference 72

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This paper cites N.; Greene, C.

Graph Neural Networks in Modern AI-aided Drug Discovery N.; Greene, C

Reference 73

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This paper cites Toward better drug discovery with knowledge graph.

Graph Neural Networks in Modern AI-aided Drug Discovery Toward better drug discovery with knowledge graph

Reference 74

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This paper cites 2021, 49 (D1), D884-D891.

Graph Neural Networks in Modern AI-aided Drug Discovery 2021, 49 (D1), D884-D891

Reference 75

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Graph Neural Networks in Modern AI-aided Drug Discovery 2024, 52 (D1), D1265-D1275

Reference 76

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This paper cites Drug Repurposing for COVID-19 via Knowledge Graph Completion.

Graph Neural Networks in Modern AI-aided Drug Discovery Drug Repurposing for COVID-19 via Knowledge Graph Completion

Reference 80

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This paper cites K.; Nová č ek, V.

Graph Neural Networks in Modern AI-aided Drug Discovery K.; Nová č ek, V

Reference 81

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This paper cites Translating embeddings for modeling multi-relational data.

Graph Neural Networks in Modern AI-aided Drug Discovery Translating embeddings for modeling multi-relational data

Reference 82

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This paper cites r-GAT: Relational Graph Attention Network for Multi-Relational Graphs.

Graph Neural Networks in Modern AI-aided Drug Discovery r-GAT: Relational Graph Attention Network for Multi-Relational Graphs

Reference 83

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This paper cites DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations.

Graph Neural Networks in Modern AI-aided Drug Discovery DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations

Reference 84

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This paper cites Network -principled deep generative models for designing drug combinations as graph sets.

Graph Neural Networks in Modern AI-aided Drug Discovery Network -principled deep generative models for designing drug combinations as graph sets

Reference 87

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Observation 5f0aebcd-60fe-4ed6-9017-203b393f7e29 · outbound

This paper cites Modeling polypharmacy side effects with graph convolutional networks.

Graph Neural Networks in Modern AI-aided Drug Discovery Modeling polypharmacy side effects with graph convolutional networks

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.614196Z

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Observation 6e283058-0cdb-4832-8ac5-06917688a8af · outbound

This paper cites RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space.

Graph Neural Networks in Modern AI-aided Drug Discovery RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

Reference 90

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Observation ecf2088b-b730-49f3-83fa-96fa0ea4c06e · outbound

This paper cites Integrating multi-modal deep learning on knowledge graph for the discovery of synergistic drug combinations against infectious diseases.

Graph Neural Networks in Modern AI-aided Drug Discovery Integrating multi-modal deep learning on knowledge graph for the discovery of synergistic drug combinations against infectious diseases

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.597944Z

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Observation 2ec320c6-c9f1-47e1-b8ad-3fe7ed433cdf · outbound

This paper cites T.; Filipek, J.; Zhang, W.

Graph Neural Networks in Modern AI-aided Drug Discovery T.; Filipek, J.; Zhang, W

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.571941Z

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Observation fab303c2-5a5c-4d4c-bcc5-24d5a8bd147e · outbound

This paper cites Positive - unlabeled learning in bioinformatics and computational biology: a brief review.

Graph Neural Networks in Modern AI-aided Drug Discovery Positive - unlabeled learning in bioinformatics and computational biology: a brief review

Reference 99

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Observation 23a50b3f-c3f2-4647-acf9-aefe1bde2322 · outbound

This paper cites The open world assumption.

Graph Neural Networks in Modern AI-aided Drug Discovery The open world assumption

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.535111Z

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Observation b0a3b6f8-0c86-427e-b780-ab7d11f20a66 · outbound

This paper cites P.; Law, J.; Mirzazadeh, M.; Ravitz, O.; Simon, A.

Graph Neural Networks in Modern AI-aided Drug Discovery P.; Law, J.; Mirzazadeh, M.; Ravitz, O.; Simon, A

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.525865Z

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Observation 674c428c-23dc-4a90-87ef-54a7361fb9bf · outbound

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Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 102

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:50:59.517003Z

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Observation 6a7380c6-57ad-4981-8815-ccc5f4dacb16 · outbound

This paper cites T.; Estrada, J.

Graph Neural Networks in Modern AI-aided Drug Discovery T.; Estrada, J

Reference 103

Resolution: verified exact; doi, observed 2026-08-07T05:50:59.508035Z

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Observation 4d8a4754-3360-4105-a526-73f855b3b3c9 · outbound

This paper cites Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions.

Graph Neural Networks in Modern AI-aided Drug Discovery Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions

Reference 107

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:50:58.977505Z

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This paper cites R.; Cui, A.

Graph Neural Networks in Modern AI-aided Drug Discovery R.; Cui, A

Reference 108

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.479392Z

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Observation 3c3767de-39c5-4ef6-a9a9-10fb7fc0af2e · outbound

This paper cites -S.; Kang, S.

Graph Neural Networks in Modern AI-aided Drug Discovery -S.; Kang, S

Reference 109

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.469337Z

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Observation aa9e6e2b-65c3-4a11-8414-0ee4d0ca38d0 · outbound

This paper cites -L.; Gulbahce, N.; Loscalzo, J.

Graph Neural Networks in Modern AI-aided Drug Discovery -L.; Gulbahce, N.; Loscalzo, J

Reference 203

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.543310Z

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Observation d04aa2d6-7292-4fb4-80fb-f524980e6cff · outbound

This paper cites M.; Arze, C.; Nadendla, S.; Chang, Y.-W.

Graph Neural Networks in Modern AI-aided Drug Discovery M.; Arze, C.; Nadendla, S.; Chang, Y.-W

Reference 265

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.707605Z

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Observation b6757afe-5266-47eb-8a62-52f14f5b087e · outbound

This paper cites Geometric interaction graph neural network for predicting protein–ligand binding affinities from 3d structures (gign).

Graph Neural Networks in Modern AI-aided Drug Discovery Geometric interaction graph neural network for predicting protein–ligand binding affinities from 3d structures (gign)

Reference 378

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Observation 414790ef-7842-463f-bd84-0ca01b28dd15 · outbound

This paper cites Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction.

Graph Neural Networks in Modern AI-aided Drug Discovery Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction

Reference 641

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:50:59.356540Z

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Observation c6c5e3b8-ab28-4f2f-b24c-f73b50e451ba · outbound

This paper cites Genome -scale annotation of protein binding sites via language model and geometric deep learning.

Graph Neural Networks in Modern AI-aided Drug Discovery Genome -scale annotation of protein binding sites via language model and geometric deep learning

Reference 739

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:56.263944Z

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Observation a9e7ae56-3c08-49dc-8e57-92428642d7f0 · outbound

This paper cites M.; Banck, M.; James, C.

Graph Neural Networks in Modern AI-aided Drug Discovery M.; Banck, M.; James, C

Reference 973

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.802887Z

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Observation c331dc5c-7624-4647-b223-3e48e3be6118 · outbound

This paper cites P.; Tiwary, P.

Graph Neural Networks in Modern AI-aided Drug Discovery P.; Tiwary, P

Reference 1053

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:56.057715Z

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This paper cites Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge.

Graph Neural Networks in Modern AI-aided Drug Discovery Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge

Reference 1071

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:58.049221Z

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Observation be7cae0a-269b-4d62-9a49-215dda9a48b3 · outbound

This paper cites A.; Norinder, U.; Spjuth, O.

Graph Neural Networks in Modern AI-aided Drug Discovery A.; Norinder, U.; Spjuth, O

Reference 1603

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:54.838459Z

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Observation 100a7656-4db7-426c-a515-858b67abc09c · outbound

This paper cites CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph.

Graph Neural Networks in Modern AI-aided Drug Discovery CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph

Reference 1741

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:58.737092Z

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Observation e250c401-9ced-4378-a8cd-45daddb9805b · outbound

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Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 1953

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:55.480129Z

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Observation d089dcc3-3b19-4291-ab5e-35c6e62eb4cc · outbound

This paper cites TP53 mutations in human cancers: origins, consequences, and clinical use.

Graph Neural Networks in Modern AI-aided Drug Discovery TP53 mutations in human cancers: origins, consequences, and clinical use

Reference 1978

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.688100Z

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Observation 6b23bfdc-c89d-4fb1-8bfe-7645c045b125 · outbound

This paper cites Using LeDock as a docking tool for computational drug design.

Graph Neural Networks in Modern AI-aided Drug Discovery Using LeDock as a docking tool for computational drug design

Reference 2001

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:56.577779Z

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Observation e795e034-0f9c-4fa5-a07b-d375ea55c6b2 · outbound

This paper cites Deep retrosynthetic reaction prediction using local reactivity and global attention.

Graph Neural Networks in Modern AI-aided Drug Discovery Deep retrosynthetic reaction prediction using local reactivity and global attention

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.498548Z

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Observation ffb836be-6387-4ce9-ae3f-105c4fd642c3 · outbound

This paper cites A Generative Model For Electron Paths.

Graph Neural Networks in Modern AI-aided Drug Discovery A Generative Model For Electron Paths

Reference 2012

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:50:58.990600Z

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Observation ee983bfe-a690-4d22-9e57-efa82305848b · outbound

This paper cites A.; Lin, Z.; Brandt, J.; Shen, X.; Sclaroff, S.

Graph Neural Networks in Modern AI-aided Drug Discovery A.; Lin, Z.; Brandt, J.; Shen, X.; Sclaroff, S

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:55.192524Z

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Unavailable: canonical work link unavailable.

Observation 38236b08-a7f7-4f2a-a0a3-f24f84eb2ea0 · outbound

This paper cites Interpretable deep learning in drug discovery.

Graph Neural Networks in Modern AI-aided Drug Discovery Interpretable deep learning in drug discovery

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:55.793945Z

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Observation 9e2c562c-a75b-4a89-9426-e302fbf59db0 · outbound

This paper cites Deeply learning molecular structure-property relationships using attention- and gate-augmented graph convolutional network.

Graph Neural Networks in Modern AI-aided Drug Discovery Deeply learning molecular structure-property relationships using attention- and gate-augmented graph convolutional network

Reference 2019

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:50:59.406887Z

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Observation b3f82b20-1775-45df-abb2-42eff7694c73 · outbound

This paper cites On explainability of graph neural networks via subgraph explorations.

Graph Neural Networks in Modern AI-aided Drug Discovery On explainability of graph neural networks via subgraph explorations

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:55.342174Z

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Observation 5170cd95-462b-499f-b6f3-52729a0c99b1 · outbound

This paper cites Prottrans: Toward understanding the language of life through self - supervised learning.

Graph Neural Networks in Modern AI-aided Drug Discovery Prottrans: Toward understanding the language of life through self - supervised learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:56.453773Z

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Unavailable: canonical work link unavailable.

Observation f1dc211f-4fcf-4fe2-b72e-b332ce060da0 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Graph Neural Networks in Modern AI-aided Drug Discovery Categorical Reparameterization with Gumbel-Softmax

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:55.451632Z

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Observation 5741983a-cee0-4b85-b0d3-9ed4ffc4f316 · outbound

This paper cites Pre-Training on Large-Scale Generated Docking Conformations with HelixDock to Unlock the Potential of Protein-ligand Structure Prediction Models.

Graph Neural Networks in Modern AI-aided Drug Discovery Pre-Training on Large-Scale Generated Docking Conformations with HelixDock to Unlock the Potential of Protein-ligand Structure Prediction Models

Reference 2023

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:50:59.385149Z

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Observation 8f46223a-6407-4f75-8b3c-e7a91b18ca33 · outbound

This paper cites R.; Morey-Burrows, F.

Graph Neural Networks in Modern AI-aided Drug Discovery R.; Morey-Burrows, F

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:57.631584Z

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Unavailable: canonical work link unavailable.

Observation 335716b1-ee59-49f8-b958-f6494006e84d · outbound

This paper cites Is Attention Interpretable?.

Graph Neural Networks in Modern AI-aided Drug Discovery Is Attention Interpretable?

Reference 2092

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:55.586503Z

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Observation 7ba27dbd-8802-44a9-a9e7-c4aa4587a4f6 · outbound

This paper cites Drug repositioning based on the heterogeneous information fusion graph convolutional network.

Graph Neural Networks in Modern AI-aided Drug Discovery Drug repositioning based on the heterogeneous information fusion graph convolutional network

Reference 2117

Resolution: verified exact; doi, observed 2026-08-07T05:50:58.965330Z

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Observation b97b9580-8893-464d-bce9-a5764d40cebb · outbound

This paper cites an unresolved cited work.

Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 2175

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:56.143253Z

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Unavailable: canonical work link unavailable.

Observation 605fe8d9-2688-445a-aeb2-c1dc720d9d40 · outbound

This paper cites KGANSynergy: knowledge graph attention network for drug synergy prediction.

Graph Neural Networks in Modern AI-aided Drug Discovery KGANSynergy: knowledge graph attention network for drug synergy prediction

Reference 2345

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.635440Z

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Observation 912e3f15-064a-4198-bfa7-ecbccb16afbe · outbound

This paper cites Generative causal explanations for graph neural networks.

Graph Neural Networks in Modern AI-aided Drug Discovery Generative causal explanations for graph neural networks

Reference 2585

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:55.443792Z

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Observation 2ef99b95-fdff-4b24-87ec-c4632f343a30 · outbound

This paper cites Pocketflow is a data -and-knowledge-driven structure-based molecular generative model.

Graph Neural Networks in Modern AI-aided Drug Discovery Pocketflow is a data -and-knowledge-driven structure-based molecular generative model

Reference 2688

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:59.784777Z

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Observation fcad3f90-6674-472d-a376-9be586e348b7 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks in Modern AI-aided Drug Discovery Unresolved cited work

Reference 2807

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:50:59.698075Z

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