AIMC Topic: High-Throughput Screening Assays

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Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation.

Cell death & disease Dec 17, 2021
Therapies halting the progression of fibrosis are ineffective and limited. Activated myofibroblasts are emerging as important targets in the progression of fibrotic diseases. Previously, we performed a high-throughput screen on lung fibroblasts and s...
Animals Drug Discovery Mice Idiopathic Pulmonary Fibrosis Humans Machine Learning Cell Differentiation Lung Diseases Transfection High-Throughput Screening Assays Bleomycin Myofibroblasts Drug Screening Assays, Antitumor
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Categorical Matrix Completion With Active Learning for High-Throughput Screening.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
The recent advances in wet-lab automation enable high-throughput experiments to be conducted seamlessly. In particular, the exhaustive enumeration of all possible conditions is always involved in high-throughput screening. Nonetheless, such a screeni...
High-Throughput Screening Assays Algorithms Proteins Computer Simulation Supervised Machine Learning Computational Biology
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Integrating deep learning with microfluidics for biophysical classification of sickle red blood cells adhered to laminin.

PLoS computational biology Nov 29, 2021
Sickle cell disease, a genetic disorder affecting a sizeable global demographic, manifests in sickle red blood cells (sRBCs) with altered shape and biomechanics. sRBCs show heightened adhesive interactions with inflamed endothelium, triggering painfu...
Humans Neural Networks, Computer Computational Biology Microfluidics Anemia, Sickle Cell High-Throughput Screening Assays Diagnosis, Computer-Assisted Deep Learning In Vitro Techniques Erythrocyte Deformability Laminin Hemoglobin, Sickle Protein Multimerization Erythrocytes, Abnormal Image Interpretation, Computer-Assisted Biophysical Phenomena Lab-On-A-Chip Devices
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Image-guided MALDI mass spectrometry for high-throughput single-organelle characterization.

Nature methods Sep 30, 2021
Peptidergic dense-core vesicles are involved in packaging and releasing neuropeptides and peptide hormones-critical processes underlying brain, endocrine and exocrine function. Yet, the heterogeneity within these organelles, even for morphologically ...
Animals Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization High-Throughput Screening Assays Organelles Machine Learning Aplysia
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ECNet is an evolutionary context-integrated deep learning framework for protein engineering.

Nature communications Sep 30, 2021
Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited....
Sequence Homology, Amino Acid beta-Lactam Resistance Genetic Fitness High-Throughput Screening Assays Datasets as Topic Protein Engineering Mutation Amino Acid Sequence beta-Lactamases Deep Learning Evolution, Molecular
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Misic, a general deep learning-based method for the high-throughput cell segmentation of complex bacterial communities.

eLife Sep 9, 2021
Studies of bacterial communities, biofilms and microbiomes, are multiplying due to their impact on health and ecology. Live imaging of microbial communities requires new tools for the robust identification of bacterial cells in dense and often inter-...
Species Specificity Microscopy High-Throughput Screening Assays Bacterial Physiological Phenomena Models, Biological Microbiota Deep Learning Biofilms
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MCN-CPI: Multiscale Convolutional Network for Compound-Protein Interaction Prediction.

Biomolecules Jul 29, 2021
In the process of drug discovery, identifying the interaction between the protein and the novel compound plays an important role. With the development of technology, deep learning methods have shown excellent performance in various situations. Howeve...
Drugs, Investigational Kinetics High-Throughput Screening Assays Datasets as Topic Deep Learning Protein Conformation, alpha-Helical Humans Binding Sites Protein Binding Protein Conformation, beta-Strand Molecular Docking Simulation Protein Interaction Domains and Motifs Proteins Drug Discovery
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The Trifecta of Single-Cell, Systems-Biology, and Machine-Learning Approaches.

Genes Jul 20, 2021
Together, single-cell technologies and systems biology have been used to investigate previously unanswerable questions in biomedicine with unparalleled detail. Despite these advances, gaps in analytical capacity remain. Machine learning, which has re...
Algorithms Precision Medicine Animals Humans Machine Learning Drug Discovery Systems Biology Single-Cell Analysis High-Throughput Screening Assays Computational Biology
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Quick Annotator: an open-source digital pathology based rapid image annotation tool.

The journal of pathology. Clinical research Jul 19, 2021
Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) in digital pathology whole slide images (WSIs). Unfortunately, annotating each structure of interest...
Biopsy Workflow Microscopy Cell Nucleus Pathology High-Throughput Screening Assays Image Interpretation, Computer-Assisted Time Factors Epithelial Cells Predictive Value of Tests Humans Reproducibility of Results Automation, Laboratory Colorectal Neoplasms Deep Learning
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Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning.

Chemical reviews Jul 14, 2021
Transition-metal complexes are attractive targets for the design of catalysts and functional materials. The behavior of the metal-organic bond, while very tunable for achieving target properties, is challenging to predict and necessitates searching a...
Coordination Complexes Transition Elements Machine Learning Metals High-Throughput Screening Assays
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