AIMC Topic: Drug Discovery

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Developing Role for Artificial Intelligence in Drug Discovery in Drug Design, Development, and Safety Assessment.

Chemical research in toxicology Sep 30, 2022
Artificial intelligence (AI) is a rapidly growing discipline in the field of chemical toxicology. Herein, we provide a broad overview of research presented at the Fall 2022 American Chemical Society meeting, highlighting how AI is being applied acros...
Drug Design Drug Discovery Artificial Intelligence
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Adera2.0: A Drug Repurposing Workflow for Neuroimmunological Investigations Using Neural Networks.

Molecules (Basel, Switzerland) Sep 30, 2022
Drug repurposing in the context of neuroimmunological (NI) investigations is still in its primary stages. Drug repurposing is an important method that bypasses lengthy drug discovery procedures and focuses on discovering new usages for known medicati...
Workflow Neural Networks, Computer Data Mining Drug Discovery Drug Repositioning
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An interpretable machine learning model for selectivity of small-molecules against homologous protein family.

Future medicinal chemistry Sep 28, 2022
In the early stages of drug discovery, various experimental and computational methods are used to measure the specificity of small molecules against a target protein. The selectivity of small molecules remains a challenge leading to off-target side ...
Machine Learning Neural Networks, Computer Proteins Receptors, Dopamine Drug Discovery
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A novel hybrid framework for metabolic pathways prediction based on the graph attention network.

BMC bioinformatics Sep 28, 2022
BACKGROUND: Making clear what kinds of metabolic pathways a drug compound involves in can help researchers understand how the drug is absorbed, distributed, metabolized, and excreted. The characteristics of a compound such as structure, composition a...
Pharmaceutical Preparations Metabolic Networks and Pathways Drug Discovery Deep Learning Machine Learning
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How do we further enhance 2D fingerprint similarity searching for novel drug discovery?

Expert opinion on drug discovery Sep 27, 2022
Artificial Intelligence Drug Discovery Humans
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MultiscaleDTA: A multiscale-based method with a self-attention mechanism for drug-target binding affinity prediction.

Methods (San Diego, Calif.) Sep 23, 2022
The task of predicting drug-target affinity (DTA) plays an increasingly important role in the early stage of in silico drug discovery and development. Currently, a variety of machine learning-based methods have been presented for DTA prediction and a...
Machine Learning Neural Networks, Computer Drug Development Drug Discovery
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Modeling DTA by Combining Multiple-Instance Learning with a Private-Public Mechanism.

International journal of molecular sciences Sep 22, 2022
The prediction of the strengths of drug-target interactions, also called drug-target binding affinities (DTA), plays a fundamental role in facilitating drug discovery, where the goal is to find prospective drug candidates. With the increase in the nu...
Drug Discovery Drug Development Machine Learning Algorithms Proteins
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GCMM: graph convolution network based on multimodal attention mechanism for drug repurposing.

BMC bioinformatics Sep 13, 2022
BACKGROUND: The main focus of in silico drug repurposing, which is a promising area for using artificial intelligence in drug discovery, is the prediction of drug-disease relationships. Although many computational models have been proposed recently, ...
Semantics Drug Repositioning Drug Discovery Artificial Intelligence
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Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.

International journal of molecular sciences Sep 8, 2022
In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a dee...
Drug Design Drug Discovery Biomarkers, Tumor Gene Expression Regulation, Neoplastic Squamous Cell Carcinoma of Head and Neck Systems Biology Deep Learning Gefitinib Humans Carcinoma, Squamous Cell Metformin Biomarkers NF-kappa B Head and Neck Neoplasms Mouth Neoplasms
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GeneralizedDTA: combining pre-training and multi-task learning to predict drug-target binding affinity for unknown drug discovery.

BMC bioinformatics Sep 7, 2022
BACKGROUND: Accurately predicting drug-target binding affinity (DTA) in silico plays an important role in drug discovery. Most of the computational methods developed for predicting DTA use machine learning models, especially deep neural networks, and...
Neural Networks, Computer Drug Discovery Proteins Drug Delivery Systems Machine Learning
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