AIMC Topic: High-Throughput Screening Assays

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Boosting Granular Support Vector Machines for the Accurate Prediction of Protein-Nucleotide Binding Sites.

Combinatorial chemistry & high throughput screening Jan 1, 2019
AIM AND OBJECTIVE: The accurate identification of protein-ligand binding sites helps elucidate protein function and facilitate the design of new drugs. Machine-learning-based methods have been widely used for the prediction of protein-ligand binding ...
Nucleotides High-Throughput Screening Assays Binding Sites Support Vector Machine Proteins
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Intelligently Applying Artificial Intelligence in Chemoinformatics.

Current topics in medicinal chemistry Jan 1, 2018
The intertwining of chemoinformatics with artificial intelligence (AI) has given a tremendous fillip to the field of drug discovery. With the rapid growth of chemical data from high throughput screening and combinatorial synthesis, AI has become an i...
Artificial Intelligence Machine Learning High-Throughput Screening Assays Quantitative Structure-Activity Relationship Algorithms Drug Discovery Data Mining
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Know When You Don't Know: A Robust Deep Learning Approach in the Presence of Unknown Phenotypes.

Assay and drug development technologies Jan 1, 2018
Deep convolutional neural networks show outstanding performance in image-based phenotype classification given that all existing phenotypes are presented during the training of the network. However, in real-world high-content screening (HCS) experimen...
Deep Learning Bayes Theorem High-Throughput Screening Assays Neural Networks, Computer Monte Carlo Method Phenotype
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Quality Control for High-Throughput Imaging Experiments Using Machine Learning in Cellprofiler.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2018
Robust high-content screening of visual cellular phenotypes has been enabled by automated microscopy and quantitative image analysis. The identification and removal of common image-based aberrations is critical to the screening workflow. Out-of-focus...
High-Throughput Screening Assays Software Cells, Cultured Image Processing, Computer-Assisted Machine Learning Microscopy Quality Control Molecular Imaging
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CAPi: Computational Model for Apicoplast Inhibitors Prediction Against Plasmodium Parasite.

Current computer-aided drug design Nov 10, 2017
BACKGROUND: Discovery of apicoplast as a drug target offers a new direction in the development of novel anti-malarial compounds, especially against the drug-resistant strains. Drugs such as azithromycin were reported to block the apicoplast developme...
Drug Discovery Malaria Models, Biological Software Algorithms Computer Simulation Plasmodium Antimalarials High-Throughput Screening Assays Databases, Pharmaceutical Humans Machine Learning
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The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology.

Oncotarget Feb 14, 2017
Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first applic...
MCF-7 Cells High-Throughput Screening Assays K562 Cells Drug Therapy Antineoplastic Agents Humans Cell Line, Tumor Neural Networks, Computer Drug Screening Assays, Antitumor Machine Learning Reproducibility of Results
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Cheminformatics Based Machine Learning Approaches for Assessing Glycolytic Pathway Antagonists of Mycobacterium tuberculosis.

Combinatorial chemistry & high throughput screening Jan 1, 2016
BACKGROUND: Tuberculosis is the second leading cause of death from an infectious disease worldwide after HIV, thus reasoning the expeditions in antituberculosis research. The rising number of cases of infection by resistant forms of M. tuberculosis h...
Machine Learning Algorithms Drug Design Glycolysis Computational Biology Tuberculosis Humans Fructose-Bisphosphate Aldolase Mycobacterium tuberculosis High-Throughput Screening Assays Enzyme Inhibitors
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A novel machine learning method for cytokine-receptor interaction prediction.

Combinatorial chemistry & high throughput screening Jan 1, 2016
Most essential functions are associated with various protein-protein interactions, particularly the cytokine-receptor interaction. Knowledge of the heterogeneous network of cytokine- receptor interactions provides insights into various human physiolo...
Cytokines Protein Binding Databases, Protein High-Throughput Screening Assays Receptors, Cytokine Humans Machine Learning
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A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

Molecular bioSystems Dec 1, 2015
Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize ...
Binding Sites Protein Interaction Mapping Mouth Neoplasms High-Throughput Screening Assays Molecular Conformation Cell Line, Tumor ROC Curve Gene Regulatory Networks Humans Protein Binding Antineoplastic Agents, Phytogenic Machine Learning Computational Biology Receptors, CXCR4 Drug Discovery Gene Expression Regulation, Neoplastic Models, Molecular
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Robotic printing and drug testing of 384-well tumor spheroids.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2015
A major impediment to anti-cancer drug development is the lack of a reliable and inexpensive tumor model to test the efficacy of candidate compounds. This need has emerged due to the insufficiency of widely-used monolayer cultures to predict drug eff...
Robotics Equipment Design Polymers Antineoplastic Agents Humans Doxorubicin Triple Negative Breast Neoplasms High-Throughput Screening Assays Female Drug Screening Assays, Antitumor Spheroids, Cellular
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