AIMC Topic: Drug Discovery

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Attention-based deep learning for accurate cell image analysis.

Scientific reports Jan 8, 2025
High-content analysis (HCA) holds enormous potential for drug discovery and research, but widely used methods can be cumbersome and yield inaccurate results. Noisy and redundant signals in cell images impede accurate deep learning-based image analysi...
Image Processing, Computer-Assisted Mitochondria Humans Neural Networks, Computer Drug Discovery Deep Learning
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Semisupervised Contrastive Learning for Bioactivity Prediction Using Cell Painting Image Data.

Journal of chemical information and modeling Jan 6, 2025
Morphological profiling has recently demonstrated remarkable potential for identifying the biological activities of small molecules. Alongside the fully supervised and self-supervised machine learning methods recently proposed for bioactivity predict...
Humans Image Processing, Computer-Assisted Drug Repositioning Machine Learning Supervised Machine Learning Drug Discovery
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Data and AI-driven synthetic binding protein discovery.

Trends in pharmacological sciences Jan 3, 2025
Synthetic binding proteins (SBPs) are a class of protein binders that are artificially created and do not exist naturally. Their broad applications in tackling challenges of research, diagnostics, and therapeutics have garnered significant interest. ...
Models, Molecular Protein Engineering Computational Biology Proteins Humans Artificial Intelligence Drug Discovery Animals Protein Binding
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Unveiling key drivers of hepatocellular carcinoma: a synergistic approach with network pharmacology, machine learning-driven ligand discovery and dynamic simulations.

SAR and QSAR in environmental research Jan 3, 2025
Hepatocellular carcinoma (HCC) ranks fourth in cancer-related mortality worldwide. This study aims to uncover the genes and pathways involved in HCC through network pharmacology (NP) and to discover potential drugs via machine learning (ML)-based lig...
Network Pharmacology Liver Neoplasms Quantitative Structure-Activity Relationship Carcinoma, Hepatocellular Humans Molecular Docking Simulation Proto-Oncogene Proteins c-akt Molecular Dynamics Simulation Glycogen Synthase Kinase 3 beta Drug Discovery Ligands Machine Learning
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MIFS: An adaptive multipath information fused self-supervised framework for drug discovery.

Neural networks : the official journal of the International Neural Network Society Jan 2, 2025
The production of expressive molecular representations with scarce labeled data is challenging for AI-driven drug discovery. Mainstream studies often follow a pipeline that pre-trains a specific molecular encoder and then fine-tunes it. However, the ...
Humans Neural Networks, Computer Supervised Machine Learning Drug Discovery
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Drug repositioning for Parkinson's disease: An emphasis on artificial intelligence approaches.

Ageing research reviews Jan 2, 2025
Parkinson's disease (PD) is one of the most incapacitating neurodegenerative diseases (NDDs). PD is the second most common NDD worldwide which affects approximately 1-2 percent of people over 65 years. It is an attractive pursuit for artificial intel...
Drug Repositioning Antiparkinson Agents Humans Artificial Intelligence Drug Discovery Parkinson Disease Machine Learning
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Drug molecular representations for drug response predictions: a comprehensive investigation via machine learning methods.

Scientific reports Jan 2, 2025
The integration of drug molecular representations into predictive models for Drug Response Prediction (DRP) is a standard procedure in pharmaceutical research and development. However, the comparative effectiveness of combining these representations ...
Humans Machine Learning Deep Learning Drug Repositioning Pharmaceutical Preparations Precision Medicine Drug Discovery
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Deep learning-based discovery of compounds for blood pressure lowering effects.

Scientific reports Jan 2, 2025
The hypotensive side effects caused by drugs during their use have been a vexing issue. Recent studies have found that deep learning can effectively predict the biological activity of compounds by mining patterns and rules in the data, providing a po...
Deep Learning Molecular Docking Simulation Hypertension Drug Discovery Antihypertensive Agents Dogs Blood Pressure Humans Animals
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Drug discovery and mechanism prediction with explainable graph neural networks.

Scientific reports Jan 2, 2025
Apprehension of drug action mechanism is paramount for drug response prediction and precision medicine. The unprecedented development of machine learning and deep learning algorithms has expedited the drug response prediction research. However, exist...
Machine Learning Algorithms Neoplasms Humans Neural Networks, Computer Deep Learning Cell Line, Tumor Computational Biology Drug Discovery Antineoplastic Agents
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CPI-GGS: A deep learning model for predicting compound-protein interaction based on graphs and sequences.

Computational biology and chemistry Dec 29, 2024
BACKGROUND: Compound-protein interaction (CPI) is essential to drug discovery and design, where traditional methods are often costly and have low success rates. Recently, the integration of machine learning and deep learning in CPI research has shown...
Humans Proteins Drug Discovery Deep Learning
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