High-throughput Applications
High-throughput Applications - Related Videos
06:51
Recovery of Adult Zebrafish Hearts for High-throughput Applications
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Cited by 16 •
2014
Use of zebrafish for cardiovascular research is expanding towards research on adult hearts. For these applications, quick and simple isolation of cardiac tissues is key to avoid post-mortem changes and to obtain an adequate number of samples. Here, we describe a fast and reproducible method for dissecting adult zebrafish hearts.
09:44
High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes
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2015
Here we describe a cell-based reporter gene assay as a valuable tool to screen chemical libraries for compounds modulating post-transcriptional control mechanisms exerted through 3’ UTR.
06:19
High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography
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Cited by 16 •
2023
This protocol details high-throughput crystallization screening, ranging from the 1,536 microassay plate preparation to the end of a 6 week experimental time window. Details are included about the sample setup, the imaging obtained, and how users can perform analyses using an artificial intelligence-enabled graphical user interface to quickly and efficiently identify macromolecular crystallization conditions.
10:02
Applications of pHluorin for Quantitative, Kinetic and High-throughput Analysis of Endocytosis in Budding Yeast
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Cited by 18 •
2016
Accurate quantification of vesicular trafficking events often provides key insights into roles for specific proteins and the effects of mutations. This paper presents methods for using superecliptic pHluorin, a pH-sensitive GFP variant, as a tool for quantification of endocytic events in living cells using quantitative fluorescence microscopy and flow cytometry.
08:39
High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately
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Cited by 117 •
2014
We present a high-throughput image analysis software application to measure the size of three-dimensional tumor spheroids imaged with bright-field microscopy. This application provides a fast and effective way to examine the effects of therapeutic drugs on spheroids, which is beneficial for researchers who wish to use spheroids in drug screens.
FAQs
High-throughput applications gain scale by coordinating parallelized workflows, automated instrumentation, miniaturized assays, and computational analysis. Parallel processing allows many samples or conditions to be examined under standardized settings, while automation supports rapid measurement and reduces dependence on manual handling. Miniaturization helps make larger experimental designs practical, and computation converts the resulting measurements into interpretable biological patterns.
Standardization is central because comparisons across many samples are meaningful only when experimental conditions remain consistent. High-throughput systems therefore emphasize uniform assay settings, automated handling, and reproducible measurement procedures. Consistency does not eliminate biological variation; instead, it helps researchers distinguish meaningful patterns from differences introduced by the workflow, strengthening the reliability of large-scale conclusions.
Computational data analysis does more than store large datasets. It helps organize and interpret measurements from numerous samples or conditions, revealing patterns and interactions that may be difficult to recognize in smaller experiments. These analyses can connect large-scale observations to questions about cellular function, disease mechanisms, or therapeutic development, provided the experimental data are generated under comparable conditions.
Compared with a smaller experiment, a high-throughput design can survey broader combinations of samples, measurements, or experimental conditions in the same general study. This expanded coverage increases the chance of detecting relationships or candidate targets that limited sampling could miss. The tradeoff is that scale requires coordinated instrumentation and data-processing methods so the added measurements remain interpretable.
A typical workflow begins by arranging many samples or experimental conditions in a parallelized format, followed by measurement with automated instrumentation and, where appropriate, miniaturized assays. The collected results then enter computational analysis for organization and interpretation. Maintaining standardized conditions throughout these stages is important because workflow consistency supports both efficient processing and reproducible comparisons.
In biology, these applications support genomic, transcriptomic, proteomic, and drug-screening studies. They can help researchers identify patterns across biological measurements, examine interactions, and prioritize candidate targets. The same scalable strategy also contributes to studies of cellular function and disease mechanisms, while in therapeutic development it helps translate broad experimental results into directions for further investigation.