AIMC Topic: High-Throughput Screening Assays

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Machine learning and computer vision approaches for phenotypic profiling.

The Journal of cell biology
With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segme...

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii.

Journal of visualized experiments : JoVE
Systematic identification and characterization of genetic perturbations have proven useful to decipher gene function and cellular pathways. However, the conventional approaches of permanent gene deletion cannot be applied to essential genes. We have ...

High-throughput and sensitive analysis of urinary heterocyclic aromatic amines using isotope-dilution liquid chromatography-tandem mass spectrometry and robotic sample preparation system.

Analytical and bioanalytical chemistry
Heterocyclic aromatic amines (HCAA) are listed by the US Food and Drug Administration (FDA) as harmful or potentially harmful constituents of tobacco smoke. However, quantifying HCAA exposure is challenging. In this study, we developed a sensitive, p...

Fully automatized high-throughput enzyme library screening using a robotic platform.

Biotechnology and bioengineering
A fully automatized robotic platform has been established to facilitate high-throughput screening for protein engineering purposes. This platform enables proper monitoring and control of growth conditions in the microtiter plate format to ensure prec...

Active machine learning-driven experimentation to determine compound effects on protein patterns.

eLife
High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or...

Quantifying co-cultured cell phenotypes in high-throughput using pixel-based classification.

Methods (San Diego, Calif.)
Biologists increasingly use co-culture systems in which two or more cell types are grown in cell culture together in order to better model cells' native microenvironments. Co-cultures are often required for cell survival or proliferation, or to maint...

Machine Learning for High-Throughput Stress Phenotyping in Plants.

Trends in plant science
Advances in automated and high-throughput imaging technologies have resulted in a deluge of high-resolution images and sensor data of plants. However, extracting patterns and features from this large corpus of data requires the use of machine learnin...

Highly predictive support vector machine (SVM) models for anthrax toxin lethal factor (LF) inhibitors.

Journal of molecular graphics & modelling
Anthrax is a highly lethal, acute infectious disease caused by the rod-shaped, Gram-positive bacterium Bacillus anthracis. The anthrax toxin lethal factor (LF), a zinc metalloprotease secreted by the bacilli, plays a key role in anthrax pathogenesis ...

Automated, high-throughput serum glycoprofiling platform.

Integrative biology : quantitative biosciences from nano to macro
Complex carbohydrates are rapidly becoming excellent biomarker candidates because of their high sensitivity to pathological changes. However, the discovery of clinical glycobiomarkers has been slow, due to the scarcity of high-throughput glycoanalyti...