AIMC Topic: Drug Discovery

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Prediction of selective estrogen receptor beta agonist using open data and machine learning approach.

Drug design, development and therapy Jul 18, 2016
BACKGROUND: Estrogen receptors (ERs) are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, inc...
Computer Simulation Drug Discovery Quantitative Structure-Activity Relationship Humans Machine Learning Estrogen Receptor beta Databases, Factual Open Access Publishing
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A renaissance of neural networks in drug discovery.

Expert opinion on drug discovery Jul 4, 2016
INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to choose the mo...
Humans Neural Networks, Computer Drug Delivery Systems Structure-Activity Relationship Computer-Aided Design Pharmaceutical Preparations Drug Design Models, Biological Drug Discovery
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Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014-2015).

Journal of chemical information and modeling Jul 1, 2016
The renewed urgency to develop new treatments for Mycobacterium tuberculosis (Mtb) infection has resulted in large-scale phenotypic screening and thousands of new active compounds in vitro. The next challenge is to identify candidates to pursue in a ...
Bayes Theorem Tuberculosis Mycobacterium tuberculosis Mice Machine Learning Computational Biology Animals Disease Models, Animal Drug Discovery
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Design of Biomedical Robots for Phenotype Prediction Problems.

Journal of computational biology : a journal of computational molecular cell biology Jun 27, 2016
Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accur...
Humans Artificial Intelligence Prognosis Leukemia, Lymphocytic, Chronic, B-Cell Drug Discovery Software Phenotype Biomarkers Mutation Amyotrophic Lateral Sclerosis Myositis, Inclusion Body Sequence Analysis, DNA Robotics
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Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?

Expert opinion on drug discovery May 30, 2016
INTRODUCTION: Artificial neural networks (ANNs) are highly adaptive nonlinear optimization algorithms that have been applied in many diverse scientific endeavors, ranging from economics, engineering, physics, and chemistry to medical science. Notably...
Quantitative Structure-Activity Relationship Pharmaceutical Preparations Nonlinear Dynamics Neural Networks, Computer Algorithms Animals Drug Design Drug Discovery Models, Theoretical Humans
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Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics.

Journal of chemical information and modeling May 20, 2016
One of the unaddressed challenges in drug discovery is that drug potency determined in vitro is not a reliable indicator of drug activity in vivo. Accumulated evidence suggests that in vivo activity is more strongly correlated with the binding/unbind...
Static Electricity Thermodynamics Ligands Protein Conformation Drug Discovery Protein Binding Computational Biology Kinetics Molecular Dynamics Simulation Safety Machine Learning
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Effectively Identifying Compound-Protein Interactions by Learning from Positive and Unlabeled Examples.

IEEE/ACM transactions on computational biology and bioinformatics May 18, 2016
Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been d...
Databases, Protein Computational Biology Protein Interaction Mapping Humans Protein Domains Support Vector Machine Caenorhabditis elegans Proteins Pharmaceutical Preparations Drug Discovery Proteins
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Applications of Deep Learning in Biomedicine.

Molecular pharmaceutics Mar 29, 2016
Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may b...
Humans Machine Learning Biomarkers Biomedical Research Animals Drug Discovery Nerve Net
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Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development.

Drug discovery today Mar 12, 2016
External content sources such as MEDLINE(®), National Institutes of Health (NIH) grants and conference websites provide access to the latest breaking biomedical information, which can inform pharmaceutical and biotechnology company pipeline decisions...
Data Mining Information Systems Drug Discovery Natural Language Processing
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Physicochemical property profile for brain permeability: comparative study by different approaches.

Journal of drug targeting Feb 6, 2016
A comparative study of classification models of brain penetration by different approaches was carried out on a training set of 1000 chemicals and drugs, and an external test set of 100 drugs. Ten approaches were applied in this work: seven medicinal ...
Pharmaceutical Preparations Brain Central Nervous System Agents Computer Simulation Permeability Machine Learning Models, Theoretical Drug Discovery Structure-Activity Relationship
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