AIMC Topic: Drug Discovery

Clear Filters Showing 1021 to 1030 of 1566 articles

Artificial Intelligence: A Novel Approach for Drug Discovery.

Trends in pharmacological sciences Jul 3, 2019
Molecular dynamics (MD) simulations can mechanistically explain receptor function. However, the enormous data sets that they may imply can be a hurdle. Plante and colleagues (Molecules, 2019) recently described a machine learning approach to the anal...
Drug Discovery Molecular Dynamics Simulation Ligands Artificial Intelligence Machine Learning
View on PubMed DOI

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...
Chemical and Drug Induced Liver Injury Vinblastine Molecular Structure Models, Biological Gene Expression Regulation Rats, Sprague-Dawley Structure-Activity Relationship Computer Simulation Reproducibility of Results Animals Male Drug Discovery Machine Learning Rats Algorithms
View on PubMed DOI

Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout.

Journal of chemical information and modeling Jun 26, 2019
While the use of deep learning in drug discovery is gaining increasing attention, the lack of methods to compute reliable errors in prediction for Neural Networks prevents their application to guide decision making in domains where identifying unreli...
Neural Networks, Computer Machine Learning Drug Discovery
View on PubMed DOI

DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences.

PLoS computational biology Jun 14, 2019
Identification of drug-target interactions (DTIs) plays a key role in drug discovery. The high cost and labor-intensive nature of in vitro and in vivo experiments have highlighted the importance of in silico-based DTI prediction approaches. In severa...
Computational Biology Binding Sites Proteins Sequence Analysis, Protein Models, Molecular Amino Acid Sequence Computer Simulation Ligands Drug Discovery Deep Learning
View on PubMed DOI

Deep Learning in Chemistry.

Journal of chemical information and modeling Jun 13, 2019
Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns represented in t...
Neural Networks, Computer Drug Design Drug Discovery Deep Learning Chemical Phenomena Humans Cheminformatics Quantitative Structure-Activity Relationship Chemistry Techniques, Synthetic
View on PubMed DOI

A Structure-Based Drug Discovery Paradigm.

International journal of molecular sciences Jun 6, 2019
Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for fut...
Quantitative Structure-Activity Relationship Molecular Docking Simulation Drug Discovery Deep Learning
View on PubMed DOI

Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets.

Molecules (Basel, Switzerland) Jun 4, 2019
Machine learning continues to make strident advances in the prediction of desired properties concerning drug development. Problematically, the efficacy of machine learning in these arenas is reliant upon highly accurate and abundant data. These two l...
Neural Networks, Computer Machine Learning Algorithms Humans Antineoplastic Agents ROC Curve Bayes Theorem Reproducibility of Results Biomarkers, Tumor Drug Discovery Molecular Targeted Therapy Workflow Models, Biological
View on PubMed DOI

A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs.

Molecules (Basel, Switzerland) Jun 2, 2019
G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Muc...
Ligands Receptor, Serotonin, 5-HT2A Quantitative Structure-Activity Relationship Receptors, G-Protein-Coupled Molecular Dynamics Simulation Drug Design Humans Algorithms Drug Discovery Machine Learning Binding Sites Molecular Docking Simulation Protein Binding
View on PubMed DOI

Ontology mapping for semantically enabled applications.

Drug discovery today May 31, 2019
In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an increasing amount and variety of data. This is particularly important for realising the full potential...
Biological Ontologies Algorithms Humans Drug Discovery Machine Learning Semantics
View on PubMed DOI

Using artificial intelligence methods to speed up drug discovery.

Expert opinion on drug discovery May 29, 2019
: Drug discovery is the process through which potential new compounds are identified by means of biology, chemistry, and pharmacology. Due to the high complexity of genomic data, AI techniques are increasingly needed to help reduce this and aid the a...
Drug Discovery Humans Drug Repositioning Artificial Intelligence Phenotype Precision Medicine
View on PubMed DOI
Popular Topics
Recent Journals