From machine learning to deep learning: progress in machine intelligence for rational drug discovery

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Protein Function Analysis through Machine Learning

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Opportunities for pharmacoproteomics in biomarker discovery

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Computational Identification of Inhibitors Using QSAR Approach Against Nipah Virus

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Formatting biological big data for modern machine learning in drug discovery

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Machine Learning Models for the Prediction of Chemotherapy-Induced Peripheral Neuropathy

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Molecular persistent spectral image (Mol-PSI) representation for machine learning models in drug design

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Prediction and design of cyclodextrin inclusion complexes formation via machine learning-based strategies

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XAI-CNVMarker: Explainable AI-based copy number variant biomarker discovery for breast cancer subtypes

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The Contribution of Artificial Intelligence to Drug Discovery: Current Progress and Prospects for the Future

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A Flexible Laser-Induced Graphene Memristor with Volatile Switching for Neuromorphic Applications

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Discovery of Cobimetinib as a novel A-FABP inhibitor using machine learning and molecular docking-based virtual screening

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Dig information of nanogenerators by machine learning

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Data-driven interpretable analysis for polysaccharide yield prediction

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Deregulation of Chromosome Segregation and Cancer

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Putting deep learning in perspective for pest management scientists

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Earthquake-induced liquefaction hazard mapping at national-scale in Australia using deep learning techniques

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How far have decision tree models come for data mining in drug discovery?

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Novel QSAR Approach for a Regression Model of Clearance That Combines DeepSnap-Deep Learning and Conventional Machine Learning

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Intelligent Mechanochemical Design of Co-Amorphous Mixtures

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Deep Learning in Environmental Toxicology: Current Progress and Open Challenges

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Industry 4.0 technologies adoption for digital transition in drug discovery and development: A review

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Deep learning and artificial intelligence for drug discovery, application, challenge, and future perspectives

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Machine Learning Classification and Structure–Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes

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Machine Learning Models for Predicting Liver Toxicity

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Deep learning in drug discovery: a futuristic modality to materialize the large datasets for cheminformatics

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A deep learning classification approach using high spatial satellite images for detection of built-up areas in rural zones: Case study of Souss-Massa region - Morocco

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Biosynthesis of protein-based drugs using eukaryotic microalgae

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Revisiting methotrexate and phototrexate Zinc15 library-based derivatives using deep learning in-silico drug design approach

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MoDeSuS: A Machine Learning Tool for Selection of Molecular Descriptors in QSAR Studies Applied to Molecular Informatics

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The QSAR Paradigm in Fragment-Based Drug Discovery: From the Virtual Generation of Target Inhibitors to Multi-Scale Modeling

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Unraveling the energetic significance of chemical events in enzyme catalysis via machine-learning based regression approach

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Machine learning for neutron scattering at ORNL*

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Probing the molecular mechanisms of α-synuclein inhibitors unveils promising natural candidates through machine-learning QSAR, pharmacophore modeling, and molecular dynamics simulations

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Computational Methodologies in Synthesis, Preparation and Application of Antimicrobial Polymers, Biomolecules, and Nanocomposites

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Unraveling the ecotoxicity of micro(nano)plastics loaded with environmental pollutants using ensemble machine learning

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Integrating Molecular Graph Data of Drugs and Multiple -Omic Data of Cell Lines for Drug Response Prediction

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Deep Learning Promotes the Screening of Natural Products with Potential Microtubule Inhibition Activity

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VAERHNN: Voting-averaged ensemble regression and hybrid neural network to investigate potent leads against colorectal cancer

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Rapid diagnosis of membranous nephropathy based on serum and urine Raman spectroscopy combined with deep learning methods

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MERGE: A model for multi-input biomedical federated learning

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Spectrum of deep learning algorithms in drug discovery

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Exploring the Artificial Intelligence and Its Impact in Pharmaceutical Sciences: Insights Toward the Horizons Where Technology Meets Tradition

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Artificial Intelligence Driven Applications in Analytical Chemistry, Drug Discovery, and Food Science: Advancements, Outlook, and Challenges

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Research progress of artificial neural systems based on memristors

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Quantum computing in drug discovery

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