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相关概念视频

Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.6K
Proteomics01:33

Proteomics

7.4K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.4K

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相关实验视频

Updated: Jul 17, 2025

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
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Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

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CellProfiler插件 - 一个简单的图像分析平台集成容器和Python工具.

Erin Weisbart1, Callum Tromans-Coia1, Barbara Diaz-Rohrer1

  • 1Broad Institute of MIT and Harvard, Cambridge MA, USA.

ArXiv
|August 30, 2023
PubMed
概括
此摘要是机器生成的。

CellProfiler-plugins通过新的模块和容器化工具集成来增强图像分析. 此升级改进了文档和引用功能,以便更广泛的社区使用.

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Ferritinophagy: Assessing the Selective Degradation of Iron by Autophagy in Human Fibroblasts
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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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相关实验视频

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科学领域:

  • 生物图像分析分析
  • 计算生物学是一种计算生物学.
  • 科学软件开发科学软件开发

背景情况:

  • CellProfiler是一种流行的开源软件,用于可复制的生物图像分析.
  • 它的插件系统可以实现自定义模块开发,集成外部Python或容器化工具.
  • 该CellProfiler-plugins存储库托管了实验性和依赖性较重的模块.

研究的目的:

  • 为了呈现一个升级的CellProfiler-plugins存储库.
  • 为了演示在CellProfiler中访问容器化工具.
  • 改进文档,并为社区参与增加引文/参考功能.

主要方法:

  • 开发和整合新的CellProfiler模块.
  • 实施一个用于访问容器化工具的系统.
  • 改进了用户文档,并增加了引用管理功能.

主要成果:

  • 现在可以使用升级的CellProfiler-plugins存储库.
  • 提供了访问容器化工具的例子.
  • 集成了改进的文档和引用工具.

结论:

  • 升级的CellProfiler-plugins存储库更容易使用和贡献.
  • 加强与外部工具的整合和改进的可用性是关键成果.
  • 这些进步支持可复制和协作生物图像分析.