AIMC Topic: High-Throughput Screening Assays

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Opportunities and Challenges in Phenotypic Screening for Neurodegenerative Disease Research.

Journal of medicinal chemistry Jul 18, 2019
Toxic misfolded proteins potentially underly many neurodegenerative diseases, but individual targets which regulate these proteins and their downstream detrimental effects are often unknown. Phenotypic screening is an unbiased method to screen for no...
Humans Machine Learning Phenotype High-Throughput Screening Assays Clustered Regularly Interspaced Short Palindromic Repeats Cell Line, Transformed Biomedical Research Animals Neurodegenerative Diseases
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Integrated Robotic Mini Bioreactor Platform for Automated, Parallel Microbial Cultivation With Online Data Handling and Process Control.

SLAS technology Jul 9, 2019
During process development, the experimental search space is defined by the number of experiments that can be performed in specific time frames but also by its sophistication (e.g., inputs, sensors, sampling frequency, analytics). High-throughput liq...
Software Algorithms Automation, Laboratory Humans High-Throughput Screening Assays Biotechnology Miniaturization Proinsulin Isopropyl Thiogalactoside Escherichia coli Robotics Bioreactors
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Applying Deep Neural Network Analysis to High-Content Image-Based Assays.

SLAS discovery : advancing life sciences R & D Jul 8, 2019
The etiological underpinnings of many CNS disorders are not well understood. This is likely due to the fact that individual diseases aggregate numerous pathological subtypes, each associated with a complex landscape of genetic risk factors. To overco...
Humans Image Processing, Computer-Assisted Molecular Imaging High-Throughput Screening Assays Neural Networks, Computer Machine Learning Deep Learning
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Automating a Magnetic 3D Spheroid Model Technology for High-Throughput Screening.

SLAS technology Jun 21, 2019
Affordable and physiologically relevant three-dimensional (3D) cell-based assays used in high-throughput screening (HTS) are on the rise in early drug discovery. These technologies have been aided by the recent adaptation of novel microplate treatmen...
Drug Evaluation, Preclinical High-Throughput Screening Assays Magnetics Automation, Laboratory Robotics Cell Culture Techniques Spheroids, Cellular
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CiRCus: A Framework to Enable Classification of Complex High-Throughput Experiments.

Journal of proteome research Mar 22, 2019
Despite the increasing use of high-throughput experiments in molecular biology, methods for evaluating and classifying the acquired results have not kept pace, requiring significant manual efforts to do so. Here, we present CiRCus, a framework to gen...
Binding, Competitive Algorithms Protein Binding Proteomics Proteins Databases, Protein High-Throughput Screening Assays Machine Learning Software
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Deep learning for predicting toxicity of chemicals: a mini review.

Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews Mar 1, 2019
Humans and wildlife inhabit a world with panoply of natural and synthetic chemicals. Alarmingly, only a limited number of chemicals have undergone comprehensive toxicological evaluation due to limitations of traditional toxicity testing. High-through...
High-Throughput Screening Assays Deep Learning Humans Quantitative Structure-Activity Relationship Models, Chemical Toxicity Tests Neural Networks, Computer Environmental Pollutants Machine Learning
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Exploration of the nanomedicine-design space with high-throughput screening and machine learning.

Nature biomedical engineering Feb 18, 2019
Only a tiny fraction of the nanomedicine-design space has been explored, owing to the structural complexity of nanomedicines and the lack of relevant high-throughput synthesis and analysis methods. Here, we report a methodology for determining struct...
Nucleic Acids Liposomes Nanomedicine Animals High-Throughput Screening Assays Nanoparticles Humans Cell Line Machine Learning Structure-Activity Relationship Oligonucleotides Alkaline Phosphatase
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Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters.

Journal of chemical information and modeling Jan 25, 2019
Assay interference caused by small molecules continues to pose a significant challenge for early drug discovery. A number of rule-based and similarity-based approaches have been derived that allow the flagging of potentially "badly behaving compounds...
Machine Learning ROC Curve Protein Binding Proteins Databases, Pharmaceutical Models, Molecular High-Throughput Screening Assays Pharmaceutical Preparations Binding Sites Small Molecule Libraries
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Network-Based Assessment of Adverse Drug Reaction Risk in Polypharmacy Using High-Throughput Screening Data.

International journal of molecular sciences Jan 17, 2019
The risk of adverse drug reactions increases in a polypharmacology setting. High-throughput drug screening with transcriptomics applied to human cells has shown that drugs have effects on several molecular pathways, and these affected pathways may be...
Humans Neural Networks, Computer Algorithms Drug-Related Side Effects and Adverse Reactions Risk Assessment High-Throughput Screening Assays Drug Design Polypharmacy Data Interpretation, Statistical
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Clinical intelligence: New machine learning techniques for predicting clinical drug response.

Computers in biology and medicine Jan 3, 2019
Predicting the response, or sensitivity, of a clinical drug to a specific cancer type is an important research problem. By predicting the clinical drug response correctly, clinicians are able to understand patient-to-patient differences in drug sensi...
Antineoplastic Agents Gene Expression Profiling Decision Support Systems, Clinical Databases, Factual Humans Computational Biology Neoplasms Machine Learning High-Throughput Screening Assays Drug Discovery Algorithms Clinical Trials as Topic
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