Utilizing graph machine learning within drug discovery and development

Cited by (313)

Items 201–300 of 313

1. Limeade: Let integer molecular encoding aid
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2. GSDeep-DTA: A Hybrid Graph and Sequence-based Deep Learning Framework for Robust Drug-Target Affinity Prediction
   W. G. D. M. Samankula, Joanne E. Harvey, Binh P. Nguyen · 2025 · IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology
3. ATLAS-DMPNN: An Attention-Guided Topological Framework for Enhanced ADMET Property Prediction
   Shanxian Lin, Guodong Cui, Cheng Tang, Chaofeng Zhang, Yuichi Nagata, Haichuan Yang · 2025 · International Conference on New Trends in Computational Intelligence (NTCI)
4. Molecular Representations for Drug Discovery
   Leili Zhang, Alex Golts, Vanessa Lopez Garcia · 2025 · Springer handbooks
5. Graph-constructed adaptive semantic fusion for heterophilic graph contrastive learning
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6. Embracing the Digital Revolution: How Artificial Intelligence is Transforming Clinical Trials in Older Participants.
   Yaru Wang, Miao Miao, Qing-Qing Wang, Yuying Yin, Hai-Juan Zhao, Shuang Zhao, Han Yang, Xin Wang · 2026 · Drugs & Aging
7. A Narrative Review of Artificial Intelligence for Drug Repurposing: Lessons From COVID‐19 and Oncology (2020–2025)
   Alaba Bukola Ogungbite, Malusi Sibiya · 2026 · CPT: Pharmacometrics & Systems Pharmacology
8. Artificial Intelligence for Integrated Analysis of Non-Blood Biological Fluids: From Biomarker Discovery to Clinical Decision-Support Systems
   Valentina Becherucci, Francesca Romano, Edda Russo · 2026 · Diagnostics
9. From linear models to deep learning: statistical advances in genomic selection for animal breeding
   Lifei Zhang, Mingzhu Zhang, Xinle Wang, Cancan Chen, Shunzhe Wang, Yujie Zhao, Yanjun Zhang, Ruijun Wang, Yongbin Liu · 2026 · Journal of Animal Science and Biotechnology/Journal of animal science and biotechnology
10. Advances in deep learning-based 3D molecular generative models
    Shaolun Yao, Jie Song, Zunlei Feng, Lingxiang Jia, Zipeng Zhong, Mingli Song · 2022 · Scientia Sinica Chimica
11. A Learning Approach for Discovering Cost-Efficient Integrated Sourcing and Routing Strategies in E-Commerce
    Omkar Shelke, Pranavi Pathakota, Anandsingh Chauhan, Hardik Meisheri, Harshad Khadilkar, Balaraman Ravindran · 2024 · Joint International Conference on Data Science & Management of Data (CODS-COMAD)
12. The use of image graph in the medical data analyzing
    Charifa Laghridat, Mohamed Essalih, Ilham Mounir · 2023 · IEEE International Conference on Advances in Data-Driven Analytics and Intelligent Systems (ADACIS)
13. Understanding the Benefits of Deep Learning in Drug Discovery: A Scoping Review
    Masibulele Msayi, Lumka Thami. P Salamntu · 2024 · Conference on Information Communications Technology and Society (ICTAS)
14. Exploring Page-based RDMA for Irregular GPU Workloads. A case study on NVMe-backed GNN Execution
    Benjamin Wagley, Pak Markthub, James Crea, Bo Wu, Mehmet Esat Belviranli · 2024 · General Purpose Processing on Graphics Processing Units
15. ATPF: An Adaptive Temporal Perturbation Framework for Adversarial Attacks on Temporal Knowledge Graph
    Longquan Liao, Linjiang Zheng, Jiaxing Shang, Xu Li, Fengwen Chen · 2024 · IEEE Transactions on Knowledge and Data Engineering
16. MDLoader: A Hybrid Model-Driven Data Loader for Distributed Graph Neural Network Training
    Jonghyun Bae, Jong Youl Choi, Massimiliano Lupo Pasini, Kshitij R. Mehta, Pei Zhang, Khaled Z. Ibrahim · 2024 · International Conference for High Performance Computing, Networking, Storage and Analysis (SC)
17. From Static Graph Attention Generation to Dynamic Graph Attention Coefficient
    Tonni Das Jui, Mary Lauren Benton, Erich Baker · 2025 · Communications in computer and information science
18. A deep graph model for the signed interaction prediction in biological network
    Shuyi Jin, M. Zhang, Meijie Wang, Lun Yu · 2024 · Research Square
19. Wilson’s Algorithm for Randomized Linear Algebra
    Yusuf Yiğit Pılavci · 2022
20. DPPIN: A Biological Dataset of Dynamic Protein-Protein Interaction Networks.
    Dongqi Fu, Jingrui He · 2021 · arXiv (Cornell University)
21. A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Synergy, and Drug-Drug Interaction Prediction
    Benedek Rózemberczki, Stephen Bonner, Andriy Nikolov, Michaël Ughetto, Sebastian Nilsson, Eliseo Papa · 2021 · arXiv (Cornell University)
22. Multi-Task Graph Neural Network For Alzheimer’s Disease Drug Repurposing Using Knowledge Graph And Multi-Level Evidence
    Kang‐Lin Hsieh, Germán Plascencia‐Villa, Ko‐Hong Lin, George L. Perry, Xiaoqian Jiang, Yejin Kim · 2022 · Research Square
23. Utilization of Landscape of Kinases and Phosphosites To Predict Kinase-Substrate Association
    Marzieh Ayati, Serhan Yılmaz, Filipa Blasco Tavares Pereira Lopes, Mark R. Chance, Mehmet Koyutürk · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
24. Graph Machine Learning for Design of High-Octane Fuels
    Jan G. Rittig, Martin Ritzert, Artur M. Schweidtmann, Winkler, Stefanie, Jana M. Weber, Philipp Morsch, Karl Alexander Heufer, Martin Grohe, Alexander Mitsos, Manuel Dahmen · 2022 · RWTH Publications (RWTH Aachen)
25. Harnessing AI and Genomics to Accelerate Drug Discovery
    Amir Feizi, Jahir M. Gutierrez · 2022 · Future of business and finance
26. Neural Drug Discovery
    Константин Анатольевич Шмырев, Ilya Makarov · 2022 · IEEE International Symposium on Computational Intelligence and Informatics (CINTI)
27. A Heterogeneous Graph Model for Repurposing Drugs against Echinococcosis
    Gantsooj Demberel, Temuulen Dorjsuren, Yansen Su, Batjargal Dolgorsuren · 2022 · ICT Focus
28. Machine Learning-Based Rumor Controlling
    Ke Su, Priyanshi Garg, Weili Wu, Ding‐Zhu Du · 2023 · Springer optimization and its applications
29. Addressing the Limitations of Graph Neural Networks on Node-level Tasks
    Sitao Luan · 2024
30. An application of graph neural networks on topic modelling with bi-partite graphs
    Bruno Fernandes Bessa de Oliveira · 2023
31. Similarity of drug targets to human microbiome metaproteome promotes pharmacological promiscuity
    Christopher A. Beaudoin, Shannon Norget, Sharif M. Hala, Andries J. van Tonder · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
32. Artificial Intelligence: From Drug Discovery to Clinical Pharmacology
    Paola Lecca · 2024
33. MDLoader: A Hybrid Model-driven Data Loader for Distributed Deep Neural Networks Training
    Jonghyun Bae, Jong Youl Choi, Massimiliano Lupo Pasini, Kshitij R. Mehta, Khaled Z. Ibrahim · 2024 · IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum
34. Multichannel Adaptive Data Mixture Augmentation for Graph Neural Networks
    Zhonglin Ye, Lin Zhou, Mingyuan Li, Wei Zhang, Zhen Liu, Haixing Zhao · 2024 · International Journal of Data Warehousing and Mining
35. Substructure-augmented Graph Transformer for Network Representation Learning
    Zhang Hu, Shanshan Yang, Guangjun Zhang, Kunrui Li · 2024 · International Joint Conference on Neural Networks (IJCNN)
36. MbExplainer: Multilevel bandit-based explanations for downstream models with augmented graph embeddings
    Ashkan Golgoon, R. Franks, Khashayar Filom, Arjun Ravi Kannan · 2024 · Machine-mediated learning
37. Efficiency in Medicinal Chemistry via Computational Chemistry
    Manojkumar Rajapriyan, A. Meera Moydeen, M. Syed Ali Padusha · 2025 · IGI Global eBooks
38. Beyond Histogram Comparison: Distribution-Aware Simple-Path Graph Kernels
    Wei Ye, Shuhao Tang, Hao Tian, Qijun Chen · 2025 · IEEE Transactions on Artificial Intelligence
39. Context-Aware Hierarchical Fusion for Drug Relational Learning
    Yijingxiu Lu, Yinhua Piao, Sangseon Lee, Sun Kim · 2025 · IEEE Transactions on Computational Biology and Bioinformatics
40. MolHyper: Hypergraph-enhanced Graph Network for Accurate Molecular Property Prediction
    Ya‐Wen Lin, Qinghe Yuan, Qunce Qiu, Sheng Lian · 2024 · International Conference on Information Technology in Medicine and Education
41. Introduction to Cheminformatics for Predictive Modeling
    Philipe Oliveira Fernandes, Rafael Lopes Almeida, Vinícius Gonçalves Maltarollo · 2025 · Challenges and advances in computational chemistry and physics
42. Revolutionizing Healthcare: Case Studies of AI Algorithms Transforming the Field of Medicine
    Aneesh Sharma, Rashee Sharma, Cheng-Hsing Yang · 2025 · Smart innovation, systems and technologies
43. Advancements in Drug Discovery Through Machine and Deep Learning Concepts in Early-Stage of Drug Discovery for Apoptosis
    Kushagra Saxena, Ankita Srivastava, Hemant Kumar · 2025 · International Conference on Disruptive Technologies (ICDT)
44. Gated Graph Neural Networks for Classification Task
    Amedeo Buonanno, Giovanni Di Gennaro, Armando Ospedale, Francesco Palmieri · 2025 · Smart innovation, systems and technologies
45. Stacked Meta-Model Drug Response Prediction System
    Aryan Sai Boddu, Aatifa Jan · 2025 · Research Square
46. A structural feature-based approach for comprehensive graph classification
    Safiqul Islam, Md. Nahid Hasan, Pitambar Khanra · 2025 · Journal of Computational Science
47. IMPLEMENTING ARTIFICIAL INTELLIGENCE IN DRUG RESEARCH DEVELOPMENT
    Satya Obbalareddy, Sanyogita Shahi, Anubhav Dubey · 2025 · BULLETIN OF STOMATOLOGY AND MAXILLOFACIAL SURGERY
48. Towards Efficient and Scalable Graph Neural Architectures for Large-Scale Systems
    Giancarlo Manuele, Alessia Romano, Lorenzo Bianchi, Francesca Vitale, Marco De Luca · 2025 · SSRN Electronic Journal
49. Link Prediction in Multipartite Graphs With Application to Drug Repositioning Studies
    Cheng Chen, Stephen K. Grady, Levente Dojcsak, Sally R. Ellingson, Michael Allen Langston · 2025 · IEEE Transactions on Computational Biology and Bioinformatics
50. A Cross-model Fusion-aware Framework for Optimizing (gather-matmul-scatter)s Workload
    Yaoxiu Lian, Zhihong Gou, Yibo Han, Zhongming Yu, Jiaming Xu, Sheng Yuan, Zhilin Pei, Xingcheng Zhang, Ningyi Xu, Guohao Dai · 2025 · ACM/IEEE Design Automation Conference (DAC)
51. Machine learning applications on healthcare systems
    J. Karunanithi, E. Sundaravalli · 2025 · AIP conference proceedings
52. Pathological graph self-supervised learning for clear-cell renal cell carcinoma survival prediction
    Wuchao Li, Yan Zhang, Shentao Yang, Xuetao Zhang, Pinhao Li, Rongpin Wang · 2025 · Pattern Recognition
53. A dual-layer dynamic graph summarization method based on extendable suffix fingerprints
    Qiang Liu, Longlong Zhao, He Cao, Zheng Liu · 2025 · Future Generation Computer Systems
54. AI-enhanced drug discovery and repurposing using graph models
    Sangam Ghimire, Nirjal Bhurtel, Sudan Jha · 2025 · Elsevier eBooks
55. PyrMol: A Knowledge-Structured Pyramid Graph Framework for Generalizable Molecular Property Prediction
    Yajie Li, Qichang Zhao, Jianxin Wang · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
56. BiGraph‐DTA: Predicting drug–target interactions of hepatoprotective agents with graph convolutional networks
    Arief Sartono, Bambang Riyanto Trilaksono, Sophi Damayanti, Anto Satriyo Nugroho, Firdayani Firdayani · 2025 · Quantitative Biology
57. HSampler : Optimizing Multi-GPU GNN Sampling with Collision-Avoid Selection
    Yuyang Jin, Jidong Zhai, Kezhao Huang, Weimin Zheng · 2025 · Lecture notes in computer science
58. Which plays a key role in sampling-based large-scale GNNs, sampling or iteration?
    Bo Jiang, Lijun Dong, Xiaoyue Peng, Renyao Chen, Chao Liu, Hong Liang Yao · 2025 · Neurocomputing
59. Graph Neural Networks for Cancer Mutation Analysis: A Deep Learning Approach for Biomarker Identification in Breast Cancer
    Juan Valentin Boyer, Jaafar M. Alghazo, Wordh Ul Hasan · 2025 · IEEE International Conference on Imaging Systems and Techniques (IST)
60. Prediction of interactions between the SARS-CoV-2 ORF3a protein and small-molecule ligands using the AND-System cognitive platform, graph neural networks, and molecular
    T. V. Ivanisenko, P. S. Demenkov, M. A. Kleshchev, V. A. Ivanisenko · 2025 · Vavilov Journal of Genetics and Breeding
61. From Code to Cure: Computational Strategies in Drug Repurposing
    K. P. Sijina, G. K. Rajanikant · 2025 · Springer handbooks
62. From nucleotides to numbers: a comprehensive review of RNA feature extraction methods for computational modelling
    Fatemeh Safari, Jai Justin Tree, Fatemeh Vafaee · 2025 · Briefings in Bioinformatics
63. Contrastive Learning Approaches for Drug Discovery
    Ana Sanchez-Fernandez, Gnter Klambauer · 2026 · Springer eBooks
64. Overcoming Topology Bias and Cold-Start Limitations in Drug Repurposing: A Clinical-Outcome-Aligned LLM Framework
    Ruihu Du, Mancheong FUNG, Yuanjia HU, Dongyang LIU · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
65. OptimES: Optimizing federated learning using remote embeddings for graph neural networks
    Pranjal Naman, Yogesh L. Simmhan · 2026 · Journal of Parallel and Distributed Computing
66. Graph neural networks for drug discovery: protocols and applications
    Yu Sun, Xiyue Zhao, Baocan Pang, Wenxuan Yang, Zixuan shao, Yonghui Lv, Qifeng Bai · 2026 · Elsevier eBooks
67. Novel discovery framework: harnessing adaptive learning for breakthroughs in drug development and clinical applications
    Austė Kanapeckaitė, Christopher John Peters, Arvydas Laurinavičius, Liesbet Geris · 2025 · Integrative Biology
68. Critical Assessment of ML models for ADMET Prediction in TDC leaderboards
    Ihor Koleiev, Roman Stratiichuk, Nazar Shevchuk, Mykola Melnychenko, Oleksiy Nyporko, Daniil Todoryshyn, Vladyslav Husak, Sergiy A. Starosyla, Semen O. Yesylevskyy, Алан Нафієв · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
69. Graph Neural Networks for Network-Based Biomarker Discovery in Complex Diseases
    S. Anuradha, B.L. Sujaya, Deepak Gupta, Kayumova Shakhnoza, Muyassar R. Allaberganova, Sardor Sabirov · 2025 · IEEE Global Conference on Wireless Computing and Networking (GCWCN)
70. DSA-GNAS: graph neural architecture search with deep semantic adaptation of large language models
    Siyang Xiao, Jiamin Chen, Zixiao Wu, Shuqing Wu, Jianliang Gao · 2026 · Knowledge and Information Systems
71. Robust machine learning for Graphs/Networks
    Hakim Hafidi · 2023
72. Décimatiοn hiérarchique pοur l'apprentissage sur graphes
    Stevan Stanovic · 2025
73. Advancements in Graph Representation Learning and Applications in Computational Biology
    Michail Chatzianastasis · 2025 · theses.fr (ABES)
74. An Overview of Role of Machine Learning in Drug Discovery
    Preethi Mahalingaswamy, Venkatalakshmi Ranganathan, Sasikala Chinnappan · 2026 · Research Journal of Pharmacy and Technology
75. Image processing using image graph: a new approach
    Charifa Laghridat, Mohamed Essalih, Ilham Mounir · 2026 · Multimedia Tools and Applications
76. Protein Design Enters the Artificial Intelligence Era: Foundations, Tools, and Emerging Paradigms
    Yanlin Mi, Arpit Shukla, Mark Tangney, Sabin Tabirca, Venkata V. B. Yallapragada · 2026 · Computational and Structural Biotechnology Journal
77. 29515 Future of AI-ML and Their Potential Impact on Deep Learning Applications in Medical Diagnostics and Imaging
    Himani Bhatt, Saurabh Rana, Mandeep Mittal · 2026 · De Gruyter eBooks
78. Drug Response Prediction using Deep Learning Models and Single-Cell Perturbation Data across Pan Cancer Cell Lines
    Phil Yao · 2026 · Highlights in Science Engineering and Technology
79. Machine learning–driven drug repurposing for GPR17: activity prediction via graph neural networks and multistage computational validation
    Noushin Agha Babaie, Morteza Farnia, Jahan Bakhsh Ghasemi · 2026 · Journal of Biomolecular Structure and Dynamics
80. Molecular Graph Neural Networks in Drug Discovery: A Narrative Review
    George Papadopoulos, Eleni Georgiou · 2025 · Pharmacophore
81. Beyond Random Splits: Assessing the Generalization of Graph and Vector Models for WT-Structure-Only Drug Resistance Prediction under Protein-Disjoint Evaluation
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82. Automated Drug Discovery and Custom Therapeutic Design Powered by Advanced Neural Networks and Digital Sandbox Testing
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83. ML for Personalized Drug Classification: Comparative Study Using Patient Clinical Data
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84. Network perturbation aggregation for graphon estimation
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85. Knowledge-graph attention network ChemFlow identifies modulators of EGFR
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86. Graph neural networks for bioinformatics
    Habib Izadkhah · 2026 · Elsevier eBooks
87. Graph-based drug–target interaction modeling: from representation learning to output-driven drug discovery
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88. Anticancer Phytochemicals in the Age of AI: Target Vulnerability, Tumor Pathway Dependency, Molecular Selectivity, and Safety-Aware Candidate Prioritization
    M. Islam, N. Akhter, Shamsul Alam · 2025 · International Journal of Pharmaceutical and Phytopharmacological Research
89. Machine Learning in Virtual Screening of Databases
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90. BioGraphEX: Multi-Level Explainability in Graph Neural Networks for Trustworthy Biomedical AI
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91. Link Prediction in Healthcare: A Bibliometric Analysis of Evolutionary Trajectories and Emerging Paradigms
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92. Rapid Generative Discovery of High‐Energy Molecules in Low Data Regimes Using Minimal Computational Resources
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93. Artificial Intelligence Applications in Bioenergy and Biomaterials Development via Fungal Biotechnology: Challenges and Perspectives
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94. Where Artificial Intelligence Changes Drug Discovery—and Where It Does Not: A Critical Review of Evidence, Limitations, and Translational Value
    Sophie Williams, Javier Rodriguez, Elena de Vries · 2024 · Pharmacophore
95. Graph Learning from Chemical Bonds to Therapeutic Systems: A Scoping Review of Pharmaceutical Representations and Reasoning Tasks
    Kerstin Richter, Mark Thompson, Dmitry Volkov, Cecilia Torres · 2025 · Pharmacophore
96. From Molecule to Patient: Learning Formulation Behavior across Material, Dosage-Form, Physiological, and Exposure Scales
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97. AI-enabled discovery of small molecule β-lactamase inhibitors to overcome enzyme diversity and resistance evolution
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98. Pharmacoinformatics after Deep Learning: A State-of-the-Art Review of Molecular Representations, Benchmark Design, and Generalization across Chemical Space
    Youssef Hariri, Hassan Nasser, Fatima Zahra · 2025 · International Journal Of Pharmaceutical Research And Allied Sciences
99. GraPNet: Protein-ligand interaction prediction based on graph learning
    Turgay Batbat, Seda Mürütsoy · 2026 · Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi
100. Data Foundations Multi-Omics, Imaging, and Clinical Data in AI-Driven Editing
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