Utilizing graph machine learning within drug discovery and development

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A Survey on Malware Detection with Graph Representation Learning

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Anomaly Detection in Dynamic Graphs: A Comprehensive Survey

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A review of mechanistic learning in mathematical oncology

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MACHINE LEARNING IN DRUG DISCOVERY: A CRITICAL REVIEW OF APPLICATIONS AND CHALLENGES

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HyGNN: Drug-Drug Interaction Prediction via Hypergraph Neural Network

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Explaining Link Prediction Systems based on Knowledge Graph Embeddings

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Learning Strong Graph Neural Networks with Weak Information

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Machine learning applications for therapeutic tasks with genomics data

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Graph machine learning for design of high‐octane fuels

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Node-Oriented Spectral Filtering for Graph Neural Networks

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Graph Neural Networks as a Potential Tool in Improving Virtual Screening Programs

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Deep Learning Concepts and Applications for Synthetic Biology

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Breast Cancer Classification From Digital Pathology Images via Connectivity-Aware Graph Transformer

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Unlearning Graph Classifiers with Limited Data Resources

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Automatic Calcification Morphology and Distribution Classification for Breast Mammograms With Multi-Task Graph Convolutional Neural Network

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A comprehensive review of artificial intelligence for pharmacology research

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AI-Based Computational Methods in Early Drug Discovery and Post Market Drug Assessment: A Survey

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Deep Learning‐Based Multiomics Data Integration Methods for Biomedical Application

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Dual-View Learning Based on Images and Sequences for Molecular Property Prediction

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Investigating Brain Connectivity with Graph Neural Networks and GNNExplainer

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Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications

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Uncovering hidden therapeutic indications through drug repurposing with graph neural networks and heterogeneous data

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ChemicalX: A Deep Learning Library for Drug Pair Scoring

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Computational Landscape in Drug Discovery: From AI/ML Models to Translational Application

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EKGDR: An End-to-End Knowledge Graph-Based Method for Computational Drug Repurposing

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Computational approaches in drug chemistry leveraging python powered QSPR study of antimalaria compounds by using artificial neural networks

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How artificial intelligence enables modeling and simulation of biological networks to accelerate drug discovery

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Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey

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RECOVER identifies synergistic drug combinations in vitro through sequential model optimization

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IBCS: Learning Information Bottleneck-Constrained Denoised Causal Subgraph for Graph Classification

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Binding-Adaptive Diffusion Models for Structure-Based Drug Design

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Artificial Intelligence in Drug Discovery: Integrative Advances From Data to Therapeutic Innovation

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