AIMC Topic: High-Throughput Screening Assays

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Effect of Cell-Cell Interaction on Single-Cell Behavior Revealed by a Deep Learning-Aided High-Throughput Addressable Single-Cell Coculture System.

Analytical chemistry
Cell-cell interactions are crucial for understanding various physiological and pathological processes, yet conventional population-level methods fail to disclose the heterogeneity at a single-cell resolution. Single-cell coculture systems that isolat...

High throughput recurrent pregnancy loss screening: urine metabolic fingerprints LDI-MS and machine learning.

The Analyst
Infertility is a significant challenge faced by many families worldwide, with recurrent pregnancy loss (RPL) being a prevalent cause of infertility among women. This condition causes immense emotional and physical distress for affected individuals an...

Accelerating antibody discovery and optimization with high-throughput experimentation and machine learning.

Journal of biomedical science
The integration of high-throughput experimentation and machine learning is transforming data-driven antibody engineering, revolutionizing the discovery and optimization of antibody therapeutics. These approaches employ extensive datasets comprising a...

High-content screening (HCS) workflows for FAIR image data management with OMERO.

Scientific reports
High-content screening (HCS) for bioimaging is a powerful approach to studying biological processes, enabling the acquisition of large amounts of images from biological samples. However, it generates massive amounts of metadata, making HCS experiment...

CODEX: COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbations.

Bioinformatics (Oxford, England)
MOTIVATION: High-throughput screens (HTS) provide a powerful tool to decipher the causal effects of chemical and genetic perturbations on cancer cell lines. Their ability to evaluate a wide spectrum of interventions, from single drugs to intricate dr...

[Advancements in virtual screening techniques for study of enzyme inhibitor compounds].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica
Enzymes are closely associated with the onset and progression of numerous diseases, making enzymes a primary target in innovative drug development. However, the challenge remains in identifying compounds that exhibit potent inhibitory effects on the ...

Machine Learning and Artificial Intelligence in Toxicological Sciences.

Toxicological sciences : an official journal of the Society of Toxicology
Machine learning and artificial intelligence approaches have revolutionized multiple disciplines, including toxicology. This review summarizes representative recent applications of machine learning and artificial intelligence approaches in different ...

Machine learned calibrations to high-throughput molecular excited state calculations.

The Journal of chemical physics
Understanding the excited state properties of molecules provides insight into how they interact with light. These interactions can be exploited to design compounds for photochemical applications, including enhanced spectral conversion of light to inc...

Comparative analysis of molecular fingerprints in prediction of drug combination effects.

Briefings in bioinformatics
Application of machine and deep learning methods in drug discovery and cancer research has gained a considerable amount of attention in the past years. As the field grows, it becomes crucial to systematically evaluate the performance of novel computa...