AIMC Topic: High-Throughput Screening Assays
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High-Throughput Screening and Prediction of Nucleophilicity of Amines Using Machine Learning and DFT Calculations.
Journal of chemical information and modeling
Aug 8, 2024
Nucleophilic index () as a significant parameter plays a crucial role in screening of amine catalysts. Indeed, the quantity and variety of amines are extensive. However, only limited amines exhibit an value exceeding 4.0 eV, rendering them potential...
Nanoscale single-vesicle analysis: High-throughput approaches through AI-enhanced super-resolution image analysis.
Biosensors & bioelectronics
Aug 5, 2024
The analysis of membrane vesicles at the nanoscale level is crucial for advancing the understanding of intercellular communication and its implications for health and disease. Despite their significance, the nanoscale analysis of vesicles at the sing...
Machine learning approach for high-throughput phenolic antioxidant screening in black Rice germplasm collection based on surface FTIR.
Food chemistry
Aug 2, 2024
Pigmented rice contains beneficial phenolic antioxidants but analysing them across germplasm collections is laborious and time-consuming. Here we utilised rapid surface Fourier transform infrared (FTIR) spectroscopy and machine learning algorithms (M...
Using VIS-NIR hyperspectral imaging and deep learning for non-destructive high-throughput quantification and visualization of nutrients in wheat grains.
Food chemistry
Jul 29, 2024
High-throughput and low-cost quantification of the nutrient content in crop grains is crucial for food processing and nutritional research. However, traditional methods are time-consuming and destructive. A high-throughput and low-cost method of quan...
Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes.
Scientific reports
Jul 26, 2024
Several computational methods have been developed to identify neutralizing antibodies (NAbs) covering four dengue virus serotypes (DENV-1 to DENV-4); however, limitations of the dataset and the resulting performance remain. Here, we developed a new c...
Collaborative robotics to enable ultra-high-throughput IR-MALDESI.
SLAS technology
Jul 23, 2024
Over the last 5 years, IR-MALDESI-MS (Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry) has been demonstrated for use in a range of high-throughput biochemical and cellular assays with remarkable sample acquisition ...
AI-Powered Microfluidics: Shaping the Future of Phenotypic Drug Discovery.
ACS applied materials & interfaces
Jul 17, 2024
Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to uncover effective drugs, has undergone a resurgence in recent years. The rapid advancement of artificial intelligence (AI) over the past few years presents nume...
Machine Learning-Assisted High-Throughput Identification and Quantification of Protein Biomarkers with Printed Heterochains.
Journal of the American Chemical Society
Jul 1, 2024
Advanced in vitro diagnosis technologies are highly desirable in early detection, prognosis, and progression monitoring of diseases. Here, we engineer a multiplex protein biosensing strategy based on the tunable liquid confinement self-assembly of mu...
Enabling high-throughput enzyme discovery and engineering with a low-cost, robot-assisted pipeline.
Scientific reports
Jun 24, 2024
As genomic databases expand and artificial intelligence tools advance, there is a growing demand for efficient characterization of large numbers of proteins. To this end, here we describe a generalizable pipeline for high-throughput protein purificat...
High-throughput classification of S. cerevisiae tetrads using deep learning.
Yeast (Chichester, England)
Jun 8, 2024
Meiotic crossovers play a vital role in proper chromosome segregation and evolution of most sexually reproducing organisms. Meiotic recombination can be visually observed in Saccharomyces cerevisiae tetrads using linked spore-autonomous fluorescent m...
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