AIMC Topic: Drug Discovery

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Learning with multiple pairwise kernels for drug bioactivity prediction.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: Many inference problems in bioinformatics, including drug bioactivity prediction, can be formulated as pairwise learning problems, in which one is interested in making predictions for pairs of objects, e.g. drugs and their targets. Kernel...
Humans Software Neoplasms Drug Discovery Antineoplastic Agents Cell Line, Tumor Computational Biology Signal Transduction Support Vector Machine Treatment Outcome Protein Kinases
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WDL-RF: predicting bioactivities of ligand molecules acting with G protein-coupled receptors by combining weighted deep learning and random forest.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: Precise assessment of ligand bioactivities (including IC50, EC50, Ki, Kd, etc.) is essential for virtual screening and lead compound identification. However, not all ligands have experimentally determined activities. In particular, many G...
Humans Computational Biology Receptors, G-Protein-Coupled Animals Drug Evaluation, Preclinical Drug Discovery Ligands Deep Learning
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How artificial intelligence is changing drug discovery.

Nature May 1, 2018
Efficiency, Organizational Drug Industry Automation Mice Robotics Amyotrophic Lateral Sclerosis Pattern Recognition, Automated Machine Learning Algorithms Precision Medicine Animals Neoplasms Drug Discovery Humans Artificial Intelligence
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[Artificial Intelligence in Drug Discovery].

Gan to kagaku ryoho. Cancer & chemotherapy Apr 1, 2018
According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic me...
Genome, Human Artificial Intelligence Drug Discovery Databases, Genetic Humans
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Machine learning accelerates MD-based binding pose prediction between ligands and proteins.

Bioinformatics (Oxford, England) Mar 1, 2018
MOTIVATION: Fast and accurate prediction of protein-ligand binding structures is indispensable for structure-based drug design and accurate estimation of binding free energy of drug candidate molecules in drug discovery. Recently, accurate pose predi...
Protein Binding Computational Biology Proteins Machine Learning Protein Conformation Drug Discovery Molecular Dynamics Simulation Ligands
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Deep learning for biology.

Nature Feb 22, 2018
Humans Genomics Polymorphism, Single Nucleotide Robotics Diagnostic Imaging Electronic Health Records Plants Rodentia Animals Neural Networks, Computer Biology Microscopy Drug Discovery Machine Learning Quality Control Software Image Interpretation, Computer-Assisted
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In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning.

Combinatorial chemistry & high throughput screening Jan 1, 2018
BACKGROUND: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors.
Models, Molecular Drug Discovery Quantitative Structure-Activity Relationship Support Vector Machine Molecular Structure Humans Thermodynamics Anticoagulants Linear Models Machine Learning Thrombin Computer Simulation
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A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction.

Indian journal of pharmacology Jan 1, 2018
CONTEXT: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details c...
Machine Learning Animals Drug Discovery Big Data Humans Neural Networks, Computer Receptors, Androgen Endocrine Disruptors Receptors, Estrogen Models, Theoretical Data Mining Inhibitory Concentration 50
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New Experimental and Computational Tools for Drug Discovery: Medicinal Chemistry, Molecular Docking, and Machine Learning - Part-VI.

Current topics in medicinal chemistry Jan 1, 2018
Chemistry, Pharmaceutical Machine Learning Molecular Docking Simulation Drug Discovery
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Intelligently Applying Artificial Intelligence in Chemoinformatics.

Current topics in medicinal chemistry Jan 1, 2018
The intertwining of chemoinformatics with artificial intelligence (AI) has given a tremendous fillip to the field of drug discovery. With the rapid growth of chemical data from high throughput screening and combinatorial synthesis, AI has become an i...
Artificial Intelligence Machine Learning High-Throughput Screening Assays Quantitative Structure-Activity Relationship Algorithms Drug Discovery Data Mining
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