AIMC Topic: Drug Discovery

Clear Filters Showing 1061 to 1070 of 1566 articles

Prediction of matrix metal proteinases-12 inhibitors by machine learning approaches.

Journal of biomolecular structure & dynamics Dec 24, 2018
Matrix metal proteinases-12 (MMP-12) is a hot pharmaceutical target on the treatment of many human diseases. There's a crying need for designing and finding new MMP-12 inhibitors. In this work, four machine learning approaches, support vector machine...
Drug Discovery ROC Curve Quantitative Structure-Activity Relationship Machine Learning Matrix Metalloproteinase Inhibitors Support Vector Machine Matrix Metalloproteinase 12 Molecular Structure Algorithms Reproducibility of Results
View on PubMed DOI

Disease comorbidity-guided drug repositioning: a case study in schizophrenia.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
UNLABELLED: The key to any computational drug repositioning is the availability of relevant data in machine-understandable format. While large amount of genetic, genomic and chemical data are publicly available, large-scale higher-level disease and d...
Knowledge Bases Information Storage and Retrieval Drug Discovery Natural Language Processing Genomics Antipsychotic Agents Humans Phenotype Schizophrenia Algorithms Comorbidity Drug Repositioning Databases, Factual
View on PubMed

Adverse Drug Reaction Predictions Using Stacking Deep Heterogeneous Information Network Embedding Approach.

Molecules (Basel, Switzerland) Dec 4, 2018
Inferring potential adverse drug reactions is an important and challenging task for the drug discovery and healthcare industry. Many previous studies in computational pharmacology have proposed utilizing multi-source drug information to predict drug ...
Machine Learning Algorithms Drug-Related Side Effects and Adverse Reactions Drug Discovery Neural Networks, Computer
View on PubMed DOI

The convergence of artificial intelligence and chemistry for improved drug discovery.

Future medicinal chemistry Nov 30, 2018
Chemistry Techniques, Synthetic Artificial Intelligence Drug Discovery Humans Computer-Aided Design Pharmaceutical Preparations Drug Design
View on PubMed DOI

A Neural Network QSPR Model for Accurate Prediction of Flash Point of Pure Hydrocarbons.

Molecular informatics Nov 29, 2018
The present study introduces a QSPR model to predict the flash point of pure organic compounds from diverse chemical families. We used the Maximum-Relevance Minimum-Redundancy (MRMR) as an efficient descriptor selection algorithm to select 20 the mos...
Drug Discovery Models, Chemical Quantitative Structure-Activity Relationship Hydrocarbons Neural Networks, Computer
View on PubMed DOI

Advances with support vector machines for novel drug discovery.

Expert opinion on drug discovery Nov 29, 2018
Novel drug discovery remains an enormous challenge, with various computer-aided drug design (CADD) approaches having been widely employed for this purpose. CADD, specifically the commonly used support vector machines (SVMs), can employ machine learni...
Humans Quantitative Structure-Activity Relationship Drug Discovery Support Vector Machine Machine Learning Drug Design
View on PubMed DOI

Closed-loop discovery platform integration is needed for artificial intelligence to make an impact in drug discovery.

Expert opinion on drug discovery Nov 29, 2018
Drug Development Humans Machine Learning Artificial Intelligence Drug Discovery
View on PubMed DOI

Artificial intelligence in drug development: present status and future prospects.

Drug discovery today Nov 22, 2018
Artificial intelligence (AI) uses personified knowledge and learns from the solutions it produces to address not only specific but also complex problems. Remarkable improvements in computational power coupled with advancements in AI technology could ...
Drug Industry Artificial Intelligence Drug Discovery Humans
View on PubMed DOI

Artificial intelligence for aging and longevity research: Recent advances and perspectives.

Ageing research reviews Nov 22, 2018
The applications of modern artificial intelligence (AI) algorithms within the field of aging research offer tremendous opportunities. Aging is an almost universal unifying feature possessed by all living organisms, tissues, and cells. Modern deep lea...
Animals Drug Discovery Biomarkers Biomedical Research Longevity Humans Algorithms Databases, Factual Artificial Intelligence
View on PubMed DOI

An overview of neural networks for drug discovery and the inputs used.

Expert opinion on drug discovery Nov 17, 2018
: Artificial intelligence systems based on neural networks (NNs) find rules for drug discovery according to training molecules, but first, the molecules need to be represented in certain ways. Molecular descriptors and fingerprints have been used as ...
Neural Networks, Computer Artificial Intelligence Drug Design Humans Ligands Drug Discovery Deep Learning
View on PubMed DOI
Popular Topics
Recent Journals