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Molecular Structure

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Development and Application of a Data-Driven Reaction Classification Model: Comparison of an Electronic Lab Notebook and Medicinal Chemistry Literature.

Journal of chemical information and modeling Sep 26, 2019
Reaction classification has often been considered an important task for many different applications, and has traditionally been accomplished using hand-coded rule-based approaches. However, the availability of large collections of reactions enables d...
Machine Learning Molecular Structure Models, Chemical Databases, Chemical Chemistry, Pharmaceutical
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Toxicity Prediction Method Based on Multi-Channel Convolutional Neural Network.

Molecules (Basel, Switzerland) Sep 17, 2019
Molecular toxicity prediction is one of the key studies in drug design. In this paper, a deep learning network based on a two-dimension grid of molecules is proposed to predict toxicity. At first, the van der Waals force and hydrogen bond were calcul...
Quantitative Structure-Activity Relationship Deep Learning Data Interpretation, Statistical Molecular Structure Neural Networks, Computer Algorithms
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Deep learning enables rapid identification of potent DDR1 kinase inhibitors.

Nature biotechnology Sep 2, 2019
We have developed a deep generative model, generative tensorial reinforcement learning (GENTRL), for de novo small-molecule design. GENTRL optimizes synthetic feasibility, novelty, and biological activity. We used GENTRL to discover potent inhibitors...
Mice Microsomes, Liver Rats Molecular Structure Protein Conformation Enzyme Inhibitors Discoidin Domain Receptor 1 Models, Molecular Humans Dogs Animals Drug Evaluation, Preclinical Deep Learning
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Energy-Geometry Dependency of Molecular Structures: A Multistep Machine Learning Approach.

ACS combinatorial science Aug 21, 2019
There is growing interest in estimating quantum observables while circumventing expensive computational overhead for facile in silico materials screening. Machine learning (ML) methods are implemented to perform such calculations in shorter times. He...
Computer Simulation Organic Chemicals Molecular Structure Machine Learning Databases, Chemical Thermodynamics Small Molecule Libraries Models, Chemical Quantum Theory Ions Inorganic Chemicals
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Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method.

International journal of molecular sciences Jul 22, 2019
Human immunodeficiency virus type-1 and hepatitis C virus (HIV/HCV) coinfection occurs when a patient is simultaneously infected with both human immunodeficiency virus type-1 (HIV-1) and hepatitis C virus (HCV), which is common today in certain popul...
Quantitative Structure-Activity Relationship Databases, Pharmaceutical Polypharmacology Hepatitis C HIV-1 Molecular Conformation Molecular Structure Bayes Theorem Hepacivirus Humans Machine Learning Algorithms Antiviral Agents Drug Discovery Protein Binding HIV Infections Models, Molecular Anti-HIV Agents
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Deep Reinforcement Learning for Multiparameter Optimization in Drug Design.

Journal of chemical information and modeling Jul 5, 2019
In medicinal chemistry programs it is key to design and make compounds that are efficacious and safe. This is a long, complex, and difficult multiparameter optimization process, often including several properties with orthogonal trends. New methods f...
Neural Networks, Computer Machine Learning Drug Design Drug Discovery Models, Theoretical Molecular Structure Models, Molecular
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Evaluating Polymer Representations via Quantifying Structure-Property Relationships.

Journal of chemical information and modeling Jul 3, 2019
Machine learning techniques are being applied in quantifying structure-property relationships for a wide variety of materials, where the properly represented materials play key roles. Although algorithms for representation learning are extensively st...
Models, Molecular Molecular Structure Machine Learning Polymers Structure-Activity Relationship
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Machine learning prediction of cyanobacterial toxin (microcystin) toxicodynamics in humans.

ALTEX Jul 2, 2019
Microcystins (MC) represent a family of cyclic peptides with approx. 250 congeners presumed harmful to human health due to their ability to inhibit ser/thr-proteinphosphatases (PPP), albeit all hazard and risk assessments (RA) are based on data of on...
Humans Machine Learning Computer Simulation Microcystins Phosphoprotein Phosphatases Nuclear Proteins Animal Use Alternatives Molecular Structure Models, Biological
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AGL-Score: Algebraic Graph Learning Score for Protein-Ligand Binding Scoring, Ranking, Docking, and Screening.

Journal of chemical information and modeling Jul 1, 2019
Although algebraic graph theory-based models have been widely applied in physical modeling and molecular studies, they are typically incompetent in the analysis and prediction of biomolecular properties, confirming the common belief that "one cannot ...
Databases, Protein Molecular Structure Machine Learning Algorithms Molecular Docking Simulation Drug Design Computational Biology Proteins
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Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.

Journal of chemical information and modeling Jun 28, 2019
Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most cases, showing an emerging challenge that is to accurately predict DILI in the early stage. Recently, th...
Drug Discovery Gene Expression Regulation Machine Learning Chemical and Drug Induced Liver Injury Structure-Activity Relationship Reproducibility of Results Vinblastine Rats Animals Molecular Structure Rats, Sprague-Dawley Algorithms Male Models, Biological Computer Simulation
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