AIMC Topic: Drug Discovery

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Machine Learning Systems Applied to Health Data and System.

European journal of health law May 19, 2020
The use of machine learning (ML) in medicine is becoming increasingly fundamental to analyse complex problems by discovering associations among different types of information and to generate knowledge for medical decision support. Many regulatory and...
Drug Development Decision Making Risk Management Trust Drug Discovery Safety Medical Informatics Medical Device Legislation Bias Confidentiality Malpractice Humans Machine Learning Software Precision Medicine
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Similarity-Based Methods and Machine Learning Approaches for Target Prediction in Early Drug Discovery: Performance and Scope.

International journal of molecular sciences May 19, 2020
Computational methods for predicting the macromolecular targets of drugs and drug-like compounds have evolved as a key technology in drug discovery. However, the established validation protocols leave several key questions regarding the performance a...
Machine Learning Reproducibility of Results Drug Discovery Knowledge Bases Molecular Targeted Therapy
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What's new in IBD therapy: An "omics network" approach.

Pharmacological research May 16, 2020
The industrial revolution that began in the late 1800s has resulted in dramatic changes in the environment, human lifestyle, dietary habits, social structure, and so on. Almost certainly because this rapid evolution has outpaced the ability of the bo...
History, 20th Century Drug Design Inflammatory Bowel Diseases Drug Discovery Diffusion of Innovation Humans Deep Learning Genomics History, 21st Century Animals Forecasting Gastroenterology Systems Biology Gastrointestinal Agents
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Quantitative Prediction of Hemolytic Toxicity for Small Molecules and Their Potential Hemolytic Fragments by Machine Learning and Recursive Fragmentation Methods.

Journal of chemical information and modeling May 15, 2020
Hemolytic toxicity, as one of the key toxicity endpoints for small molecules, can cause lysis of the erythrocyte membrane and subsequent release of hemoglobin into blood plasma, leading to multiple acute and chronic adverse effects. Hence, it is nece...
Humans Drug Discovery Machine Learning Drug-Related Side Effects and Adverse Reactions Software
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Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions.

Journal of computer-aided molecular design May 2, 2020
Difficulties in interpreting machine learning (ML) models and their predictions limit the practical applicability of and confidence in ML in pharmaceutical research. There is a need for agnostic approaches aiding in the interpretation of ML models re...
Humans Neural Networks, Computer Models, Molecular Pharmaceutical Preparations Machine Learning Therapeutic Equivalency Drug Discovery Structure-Activity Relationship
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Dual graph convolutional neural network for predicting chemical networks.

BMC bioinformatics Apr 23, 2020
BACKGROUND: Predicting of chemical compounds is one of the fundamental tasks in bioinformatics and chemoinformatics, because it contributes to various applications in metabolic engineering and drug discovery. The recent rapid growth of the amount of ...
Computational Biology Neural Networks, Computer Models, Chemical Drug Discovery Computer Graphics
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Parsing Molecules for Drug Discovery.

Biochemistry Apr 21, 2020
Anti-Bacterial Agents Computer Simulation Drug Discovery Algorithms Deep Learning
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Target Identification Using Homopharma and Network-Based Methods for Predicting Compounds Against Dengue Virus-Infected Cells.

Molecules (Basel, Switzerland) Apr 18, 2020
Drug target prediction is an important method for drug discovery and design, can disclose the potential inhibitory effect of active compounds, and is particularly relevant to many diseases that have the potential to kill, such as dengue, but lack any...
Computational Biology Dengue Drug Discovery Lipids Humans Antiviral Agents Dengue Virus Neural Networks, Computer Host-Pathogen Interactions Protein Interaction Maps Virus Replication Protein Interaction Mapping
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The Synthesizability of Molecules Proposed by Generative Models.

Journal of chemical information and modeling Apr 17, 2020
The discovery of functional molecules is an expensive and time-consuming process, exemplified by the rising costs of small molecule therapeutic discovery. One class of techniques of growing interest for early stage drug discovery is molecular genera...
Drug Design Neural Networks, Computer Algorithms Drug Discovery Molecular Structure
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Revealing cytotoxic substructures in molecules using deep learning.

Journal of computer-aided molecular design Apr 16, 2020
In drug development, late stage toxicity issues of a compound are the main cause of failure in clinical trials. In silico methods are therefore of high importance to guide the early design process to reduce time, costs and animal testing. Technical a...
Toxicology Small Molecule Libraries Models, Biological Cytotoxins HEK293 Cells Hep G2 Cells Cell Survival Neural Networks, Computer Software Computer-Aided Design Drug Design Drug Discovery Deep Learning Humans
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