AIMC Topic: Drug Discovery

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Artificial Intelligence Transforms the Future of Health Care.

The American journal of medicine Jan 31, 2019
Life sciences researchers using artificial intelligence (AI) are under pressure to innovate faster than ever. Large, multilevel, and integrated data sets offer the promise of unlocking novel insights and accelerating breakthroughs. Although more data...
Forecasting Delivery of Health Care Drug Discovery Decision Support Systems, Clinical Artificial Intelligence Machine Learning Humans Translational Research, Biomedical Epidemics
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Deep learning for molecular generation.

Future medicinal chemistry Jan 30, 2019
De novo drug design aims to generate novel chemical compounds with desirable chemical and pharmacological properties from scratch using computer-based methods. Recently, deep generative neural networks have become a very active research frontier in d...
Software Animals Drug Discovery Deep Learning Drug Design Humans Neural Networks, Computer
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Could advances in representation learning in Artificial Intelligence provide the new paradigm for data integration in drug discovery?

Expert opinion on drug discovery Jan 30, 2019
Drug Discovery Artificial Intelligence Machine Learning Humans Neural Networks, Computer
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Deep Learning: Current and Emerging Applications in Medicine and Technology.

IEEE journal of biomedical and health informatics Jan 23, 2019
Machine learning is enabling researchers to analyze and understand increasingly complex physical and biological phenomena in traditional fields such as biology, medicine, and engineering and emerging fields like synthetic biology, automated chemical ...
Robotics Nanomedicine Deep Learning Computational Biology Image Interpretation, Computer-Assisted Biotechnology Humans Drug Design Drug Discovery
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Computational methods and tools to predict cytochrome P450 metabolism for drug discovery.

Chemical biology & drug design Jan 15, 2019
In this review, we present important, recent developments in the computational prediction of cytochrome P450 (CYP) metabolism in the context of drug discovery. We discuss in silico models for the various aspects of CYP metabolism prediction, includin...
Drug Discovery Computational Biology Machine Learning Cytochrome P-450 Enzyme System Quantitative Structure-Activity Relationship Substrate Specificity Pharmaceutical Preparations Quantum Theory
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Exploring Tunable Hyperparameters for Deep Neural Networks with Industrial ADME Data Sets.

Journal of chemical information and modeling Jan 11, 2019
Deep learning has drawn significant attention in different areas including drug discovery. It has been proposed that it could outperform other machine learning algorithms, especially with big data sets. In the field of pharmaceutical industry, machin...
Quantitative Structure-Activity Relationship Drug Discovery Pharmaceutical Preparations Absorption, Physicochemical Deep Learning
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PathwayMap: Molecular Pathway Association with Self-Normalizing Neural Networks.

Journal of chemical information and modeling Jan 10, 2019
Drug discovery suffers from high attrition because compounds initially deemed as promising can later show ineffectiveness or toxicity resulting from a poor understanding of their activity profile. In this work, we describe a deep self-normalizing neu...
Drug Discovery Neural Networks, Computer
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eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates.

BMC pharmacology & toxicology Jan 8, 2019
BACKGROUND: The efficiency of drug development defined as a number of successfully launched new pharmaceuticals normalized by financial investments has significantly declined. Nonetheless, recent advances in high-throughput experimental techniques an...
Humans Machine Learning Algorithms Animals Drug-Related Side Effects and Adverse Reactions Drug Discovery
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Clinical intelligence: New machine learning techniques for predicting clinical drug response.

Computers in biology and medicine Jan 3, 2019
Predicting the response, or sensitivity, of a clinical drug to a specific cancer type is an important research problem. By predicting the clinical drug response correctly, clinicians are able to understand patient-to-patient differences in drug sensi...
Clinical Trials as Topic Neoplasms Drug Discovery Algorithms Databases, Factual Humans Antineoplastic Agents Computational Biology Decision Support Systems, Clinical Machine Learning Gene Expression Profiling High-Throughput Screening Assays
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Polypharmacology Browser PPB2: Target Prediction Combining Nearest Neighbors with Machine Learning.

Journal of chemical information and modeling Dec 31, 2018
Here we report PPB2 as a target prediction tool assigning targets to a query molecule based on ChEMBL data. PPB2 computes ligand similarities using molecular fingerprints encoding composition (MQN), molecular shape and pharmacophores (Xfp), and subst...
Databases, Chemical Drug Discovery Machine Learning Polypharmacology TRPV Cation Channels Software
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