AIMC Topic: Drug Design

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Opportunities and obstacles for deep learning in biology and medicine.

Journal of the Royal Society, Interface Apr 1, 2018
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine ar...
Delivery of Health Care Electronic Health Records Biomedical Research Humans Algorithms Terminology as Topic Biomedical Technology Disease Drug Design Deep Learning Decision Making
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Machine-Learning Prediction of Drug-Induced Cardiac Arrhythmia: Analysis of Gene Expression and Clustering.

Critical reviews in biomedical engineering Jan 1, 2018
A marked delay in the electrical repolarization of heart ventricles is characterized by prolongation of the Q-T wave (QT) interval on a surface electrocardiogram. Such a delay can lead to potentially life-threatening cardiac arrhythmia (torsades de p...
Clinical Trials as Topic False Positive Reactions Torsades de Pointes Arrhythmias, Cardiac MAP Kinase Signaling System Gene Expression Regulation Humans Heart Machine Learning Drug Evaluation, Preclinical Female Heart Ventricles Mice Support Vector Machine Cluster Analysis Rats Signal Processing, Computer-Assisted Male Reproducibility of Results Electrocardiography Drug Design Sensitivity and Specificity Gene Expression Profiling Animals
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Machine Learning-Based Modeling of Drug Toxicity.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2018
Toxicity is an important reason for the failure of drug research and development (R&D). The traditional experimental testings for chemical toxicity profile are costly and time-consuming. Therefore, it is attractive to develop the effective and accura...
Internet Pharmaceutical Preparations Models, Biological Drug Design Carcinogenesis Molecular Structure Sequence Homology, Amino Acid Ether-A-Go-Go Potassium Channels Drug-Related Side Effects and Adverse Reactions Ligands Quantitative Structure-Activity Relationship Humans Machine Learning Software
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Generative Models for Artificially-intelligent Molecular Design.

Molecular informatics Jan 1, 2018
Neural Networks, Computer Drug Design Drug Discovery
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Cheminformatics and the Mean.

Molecular informatics Jan 1, 2018
Drug Design Chemistry, Pharmaceutical Artificial Intelligence
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Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

Combinatorial chemistry & high throughput screening Jan 1, 2018
AIM AND OBJECTIVE: Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug d...
Binding Sites Artificial Intelligence Algorithms Drug Design Blood Proteins Humans Least-Squares Analysis Pharmaceutical Preparations
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DeepSite: protein-binding site predictor using 3D-convolutional neural networks.

Bioinformatics (Oxford, England) Oct 1, 2017
MOTIVATION: An important step in structure-based drug design consists in the prediction of druggable binding sites. Several algorithms for detecting binding cavities, those likely to bind to a small drug compound, have been developed over the years b...
Proteins Protein Conformation Binding Sites Software Algorithms Drug Design Neural Networks, Computer Machine Learning
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The drug-maker's guide to the galaxy.

Nature Sep 26, 2017
Databases, Chemical Computer Simulation Humans Drug Design Machine Learning Drug Discovery Algorithms
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Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.

Current drug discovery technologies Jan 1, 2017
BACKGROUND: Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and exc...
Models, Biological Intestinal Absorption Drug Design Humans Least-Squares Analysis Artificial Intelligence Pharmaceutical Preparations
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Improving Recognition of Antimicrobial Peptides and Target Selectivity through Machine Learning and Genetic Programming.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2017
Growing bacterial resistance to antibiotics is spurring research on utilizing naturally-occurring antimicrobial peptides (AMPs) as templates for novel drug design. While experimentalists mainly focus on systematic point mutations to measure the effec...
Gram-Negative Bacteria Neural Networks, Computer Gram-Positive Bacteria Genetic Engineering Machine Learning Algorithms Drug Design Computational Biology Decision Trees Antimicrobial Cationic Peptides
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