AIMC Topic: Drug Discovery

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Prediction of Multi-Pharmacokinetics Property in Multi-Species: Bayesian Neural Network Stacking Model with Uncertainty.

Molecular pharmaceutics Nov 7, 2024
Pharmacokinetic (PK) properties of a drug are vital attributes influencing its therapeutic effectiveness, playing an important role in the drug development process. Focusing on the difficult task of predicting PK parameters, we compiled an extensive ...
Drug Development Bayes Theorem Animals Drug Discovery Uncertainty Models, Biological Pharmacokinetics Humans Neural Networks, Computer
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Challenges and Prospects of DNA-Encoded Library Data Interpretation.

Chemical reviews Nov 7, 2024
DNA-encoded library (DEL) technology is a powerful platform for the efficient identification of novel chemical matter in the early drug discovery process enabled by parallel screening of vast libraries of encoded small molecules through affinity sele...
Small Molecule Libraries Gene Library Drug Discovery DNA Humans Machine Learning
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Unleashing the future: The revolutionary role of machine learning and artificial intelligence in drug discovery.

European journal of pharmacology Nov 6, 2024
Drug discovery is a complex and multifaceted process aimed at identifying new therapeutic compounds with the potential to treat various diseases. Traditional methods of drug discovery are often time-consuming, expensive, and characterized by low succ...
Humans Artificial Intelligence Animals Drug Discovery Machine Learning
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Drug-Target Prediction Based on Dynamic Heterogeneous Graph Convolutional Network.

IEEE journal of biomedical and health informatics Nov 6, 2024
Novel drug-target interaction (DTI) prediction is crucial in drug discovery and repositioning. Recently, graph neural network (GNN) has shown promising results in identifying DTI by using thresholds to construct heterogeneous graphs. However, an empi...
Neural Networks, Computer Humans Algorithms Computational Biology Drug Discovery Deep Learning
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ChemXTree: A Feature-Enhanced Graph Neural Network-Neural Decision Tree Framework for ADMET Prediction.

Journal of chemical information and modeling Nov 5, 2024
The rapid progression of machine learning, especially deep learning (DL), has catalyzed a new era in drug discovery, introducing innovative approaches for predicting molecular properties. Despite the many methods available for feature representation,...
Neural Networks, Computer Machine Learning Drug Discovery Decision Trees Deep Learning
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NFSA-DTI: A Novel Drug-Target Interaction Prediction Model Using Neural Fingerprint and Self-Attention Mechanism.

International journal of molecular sciences Nov 3, 2024
Existing deep learning methods have shown outstanding performance in predicting drug-target interactions. However, they still have limitations: (1) the over-reliance on locally extracted features by some single encoders, with insufficient considerati...
Humans Neural Networks, Computer Algorithms Drug Discovery Deep Learning Pharmaceutical Preparations
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AlzyFinder: A Machine-Learning-Driven Platform for Ligand-Based Virtual Screening and Network Pharmacology.

Journal of chemical information and modeling Oct 31, 2024
Alzheimer's disease (AD), a prevalent neurodegenerative disorder, presents significant challenges in drug development due to its multifactorial nature and complex pathophysiology. The AlzyFinder Platform, introduced in this study, addresses these cha...
Alzheimer Disease Machine Learning Ligands Drug Discovery User-Computer Interface Network Pharmacology Humans Drug Evaluation, Preclinical
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Impact of Artificial Intelligence on Clinical Research.

Gastrointestinal endoscopy clinics of North America Oct 29, 2024
Artificial intelligence (AI) has potential to significantly impact clinical research when it comes to research preparation and data interpretation. Development of AI tools that can help in performing literature searches, synthesizing and streamlining...
Biomedical Research Drug Discovery Humans Gastroenterology Artificial Intelligence
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Molecular tweaking by generative cheminformatics and ligand-protein structures for rational drug discovery.

Bioorganic chemistry Oct 28, 2024
The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-protein structures in directing drug discovery; (2) to present examples of drugs from the recent literatu...
Humans Artificial Intelligence Ligands Proteins Machine Learning Cheminformatics Molecular Structure Drug Discovery
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Antiviral Peptide-Generative Pre-Trained Transformer (AVP-GPT): A Deep Learning-Powered Model for Antiviral Peptide Design with High-Throughput Discovery and Exceptional Potency.

Viruses Oct 25, 2024
Traditional antiviral peptide (AVP) discovery is a time-consuming and expensive process. This study introduces AVP-GPT, a novel deep learning method utilizing transformer-based language models and multimodal architectures specifically designed for AV...
Humans Deep Learning Antiviral Agents High-Throughput Screening Assays Peptides Drug Discovery Respiratory Syncytial Viruses Drug Design Influenza A virus
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