AIMC Topic: Drug Discovery

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Designing molecules with autoencoder networks.

Nature computational science Nov 21, 2023
Autoencoders are versatile tools in molecular informatics. These unsupervised neural networks serve diverse tasks such as data-driven molecular representation and constructive molecular design. This Review explores their algorithmic foundations and a...
Neural Networks, Computer Drug Discovery
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Drug discovery: In silico dry data can bypass biological wet data?

British journal of pharmacology Nov 14, 2023
The recent and extraordinary increase in computer power, along with the availability of efficient algorithms based on artificial intelligence, has prompted a large number of inexperienced scientists to challenge the complex and yet competitive world ...
Artificial Intelligence Computer-Aided Design Drug Design Drug Discovery
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CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures.

Nature communications Nov 13, 2023
The field of bioimage analysis is currently impacted by a profound transformation, driven by the advancements in imaging technologies and artificial intelligence. The emergence of multi-modal AI systems could allow extracting and utilizing knowledge ...
Artificial Intelligence Databases, Factual Learning Drug Discovery Knowledge
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Artificial intelligence and machine learning for clinical pharmacology.

British journal of clinical pharmacology Nov 12, 2023
Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug discovery and development, clinical trials, personalized medicine, pharmacogenomics, pharmacovigilance and clinical toxicology. The rapid progress of AI in...
Humans Artificial Intelligence Machine Learning Drug Discovery Biomedical Technology Pharmacology, Clinical
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STAGAN: An approach for improve the stability of molecular graph generation based on generative adversarial networks.

Computers in biology and medicine Nov 10, 2023
With the wide application of deep learning in Drug Discovery, deep generative model has shown its advantages in drug molecular generation. Generative adversarial networks can be used to learn the internal structure of molecules, but the training proc...
Drug Discovery Deep Learning Models, Chemical
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Deep Generative Models in Drug Molecule Generation.

Journal of chemical information and modeling Nov 7, 2023
The discovery of new drugs has important implications for human health. Traditional methods for drug discovery rely on experiments to optimize the structure of lead molecules, which are time-consuming and high-cost. Recently, artificial intelligence ...
Humans Artificial Intelligence Databases, Factual Drug Design Drug Discovery Benchmarking
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Artificial intelligence: Machine learning approach for screening large database and drug discovery.

Antiviral research Nov 5, 2023
Recent research in drug discovery dealing with many faces difficulties, including development of new drugs during disease outbreak and drug resistance due to rapidly accumulating mutations. Virtual screening is the most widely used method in computer...
Artificial Intelligence Machine Learning Algorithms Databases, Factual Drug Design Drug Discovery
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Computational methods in glaucoma research: Current status and future outlook.

Molecular aspects of medicine Nov 3, 2023
Advancements in computational techniques have transformed glaucoma research, providing a deeper understanding of genetics, disease mechanisms, and potential therapeutic targets. Systems genetics integrates genomic and clinical data, aiding in identif...
Humans Glaucoma Artificial Intelligence Drug Discovery Genomics
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Automation to Enable High-Throughput Chemical Proteomics.

Journal of proteome research Nov 2, 2023
Chemical proteomics utilizes small-molecule probes to covalently engage with their interacting proteins. Since chemical probes are tagged to the active or binding sites of functional proteins, chemical proteomics can be used to profile protein target...
Artificial Intelligence Drug Discovery Proteomics Proteins Automation
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Extracting medicinal chemistry intuition via preference machine learning.

Nature communications Oct 31, 2023
The lead optimization process in drug discovery campaigns is an arduous endeavour where the input of many medicinal chemists is weighed in order to reach a desired molecular property profile. Building the expertise to successfully drive such projects...
Artificial Intelligence Machine Learning Drug Design Drug Discovery Chemistry, Pharmaceutical Intuition
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