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相关概念视频

Genetic Screens02:46

Genetic Screens

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
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Combinatorial Gene Control02:33

Combinatorial Gene Control

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Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
17.5K

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相关实验视频

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Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens
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在计算基因组学中创建和使用最小化草图.

Hongyu Zheng1, Guillaume Marçais2, Carl Kingsford2

  • 1Computer Science Department, Princeton University, Princeton, New Jersey, USA.

Journal of computational biology : a journal of computational molecular cell biology
|August 30, 2023
PubMed
概括

在计算基因组学中,最小化器素描对于处理大型基因组数据集至关重要. 本调查回顾了它的历史,理论和应用,旨在改善未来的研究.

科学领域:

  • 计算型基因组学计算型基因组学
  • 生物信息学是一种生物信息学.

背景情况:

  • 在现代基因组学中,大规模的序列数据处理是必不可少的.
  • 经典的最小化素描方法面临着随着数据量不断增加的计算挑战.

研究的目的:

  • 在计算基因组学中提供最小化素描技术的全面审查.
  • 探索最小化素描的历史,理论基础和各种应用.
  • 为了弥合最小化器草图理论和实际应用之间的差距.

主要方法:

  • 审查最小化素描算法的历史发展.
  • 分析不同最小化器素描结构的理论性质.
  • 对读取映射,序列组装和k-mer计数中的应用进行了调查.

主要成果:

  • 缩小器草图是各种计算基因组学任务的基础.
  • 最近的进展侧重于开发具有改进属性的最小化素描.
  • 广泛的应用表明了最小化素描的实用性.

结论:

  • 缩小素描是计算基因组学中至关重要的工具.
  • 预计理论和应用的进一步整合将提高最小化素描的实用性.
关键词:
德·布鲁伊恩的图表显示了k-mer正在进行计数.最小化器是最小化器.读取映射读取映射的情况绘制草图,绘制草图.

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  • 这项调查为未来的测序素描研究和开发提供了基础.