AIMC Topic: Drug Discovery

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Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks.

Drug discovery today Jun 21, 2018
Drug Discovery Deep Learning Pharmaceutical Preparations Neural Networks, Computer Algorithms Ligands Quantitative Structure-Activity Relationship Humans
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Reinforced Adversarial Neural Computer for de Novo Molecular Design.

Journal of chemical information and modeling Jun 12, 2018
In silico modeling is a crucial milestone in modern drug design and development. Although computer-aided approaches in this field are well-studied, the application of deep learning methods in this research area is at the beginning. In this work, we p...
Neural Networks, Computer Machine Learning Drug Discovery Deep Learning Equipment Design Algorithms Computer-Aided Design Drug Design
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Development of Ligand-based Big Data Deep Neural Network Models for Virtual Screening of Large Compound Libraries.

Molecular informatics Jun 8, 2018
High-performance ligand-based virtual screening (VS) models have been developed using various computational methods, including the deep neural network (DNN) method. There are high expectations for exploration of the advanced capabilities of DNN to im...
Small Molecule Libraries Databases, Chemical ErbB Receptors Humans Drug Discovery Neural Networks, Computer Big Data Molecular Docking Simulation Ligands
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Next-Generation Machine Learning for Biological Networks.

Cell Jun 7, 2018
Machine learning, a collection of data-analytical techniques aimed at building predictive models from multi-dimensional datasets, is becoming integral to modern biological research. By enabling one to generate models that learn from large datasets an...
Neural Networks, Computer Machine Learning Algorithms Humans Computational Biology Microbiota Drug-Related Side Effects and Adverse Reactions Databases, Factual Drug Discovery
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Deep Learning for Drug Discovery and Cancer Research: Automated Analysis of Vascularization Images.

IEEE/ACM transactions on computational biology and bioinformatics May 29, 2018
Likely drug candidates which are identified in traditional pre-clinical drug screens often fail in patient trials, increasing the societal burden of drug discovery. A major contributing factor to this phenomenon is the failure of traditional in vitro...
Pattern Recognition, Automated Cell Culture Techniques Deep Learning Humans Neoplasms Image Processing, Computer-Assisted Microscopy Neural Networks, Computer Drug Discovery Neovascularization, Pathologic Antineoplastic Agents Extracellular Matrix
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Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches.

BMC bioinformatics May 21, 2018
BACKGROUND: Link prediction in biomedical graphs has several important applications including predicting Drug-Target Interactions (DTI), Protein-Protein Interaction (PPI) prediction and Literature-Based Discovery (LBD). It can be done using a classif...
Drug Discovery Protein Interaction Mapping Knowledge Discovery Neural Networks, Computer Algorithms
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Network-Based Disease Module Discovery by a Novel Seed Connector Algorithm with Pathobiological Implications.

Journal of molecular biology May 20, 2018
Understanding the genetic basis of complex diseases is challenging. Prior work shows that disease-related proteins do not typically function in isolation. Rather, they often interact with each other to form a network module that underlies dysfunction...
Humans Neural Networks, Computer Algorithms Models, Biological Drug Discovery Disease Susceptibility Protein Interaction Maps Protein Interaction Mapping Databases, Protein
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Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water.

Journal of chemical information and modeling May 16, 2018
Prediction of compound properties from structure via quantitative structure-activity relationship and machine-learning approaches is an important computational chemistry task in small-molecule drug research. Though many such properties are dependent ...
Gases Informatics Machine Learning Thermodynamics Drug Discovery Molecular Conformation Water Quantitative Structure-Activity Relationship Models, Molecular Pharmaceutical Preparations Solvents
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Machine learning in chemoinformatics and drug discovery.

Drug discovery today May 8, 2018
Chemoinformatics is an established discipline focusing on extracting, processing and extrapolating meaningful data from chemical structures. With the rapid explosion of chemical 'big' data from HTS and combinatorial synthesis, machine learning has be...
Humans Machine Learning Animals Drug Discovery Molecular Structure Pharmaceutical Preparations Pattern Recognition, Automated Quantitative Structure-Activity Relationship Informatics Diffusion of Innovation High-Throughput Screening Assays
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Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization.

Journal of chemical information and modeling May 8, 2018
Undetected overfitting can occur when there are significant redundancies between training and validation data. We describe AVE, a new measure of training-validation redundancy for ligand-based classification problems, that accounts for the similarity...
Machine Learning Drug Discovery Benchmarking Ligands
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