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相关概念视频

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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...
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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
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相关实验视频

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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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维斯塔发现了缺失的基因表达和空间诱导信息,用于空间转录组数据分析.

Tianyu Liu1, Yingxin Lin2, Xiao Luo3

  • 1Interdepartmental Program in Computational Biology & Bioinformatics, Yale University, New Haven, 06511, CT, USA.

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概括
此摘要是机器生成的。

维斯塔可以预测空间转录组学 (SST) 数据中的基因表达,克服目前方法的局限性. 这种方法增强了对细胞活动在它们的空间环境中的理解.

关键词:
生成模型的生成模型计入计算是指计入计算的方法.空间转录学 空间转录学不确定性定量化 不确定性定量化变量推理 变量推理

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科学领域:

  • 空间转录学 空间转录学
  • 计算生物学 计算生物学
  • 基因组学就是基因组学.

背景情况:

  • 在空间背景下了解细胞活动对于破译组织组织和功能至关重要.
  • 单细胞RNA测序 (scRNA-seq) 提供了全面的基因表达,但缺乏空间信息.
  • 亚细胞空间转录学 (SST) 提供高分辨率的空间数据,但对有限数量的基因进行了分析.

研究的目的:

  • 开发一种新的计算方法,VISTA,用于预测空间转录组学数据中的未观察到的基因表达.
  • 为了解决当前SST技术的基因分析局限性.
  • 通过归纳缺少的基因表达数据,使得下游分析的范围更广泛.

主要方法:

  • 维斯塔利用变异推断和几何深度学习共同建模scRNA-seq和SST数据.
  • 该方法包括不确定性量化,以提供可靠的预测.
  • 该方法旨在有效分析大规模的SST数据集,同时考虑时间和内存限制.

主要成果:

  • 在四个不同的SST数据集中,VISTA在基因表达赋值方面表现出卓越的性能.
  • 该方法在大规模数据分析中显示出令人满意的时间效率和内存消耗.
  • 导入的数据使得新的下游应用成为可能,包括检测空间变量的基因和连接体-受体相互作用.

结论:

  • 维斯塔有效地预测了空间转录组学数据中的基因表达,弥合了scRNA-seq和SST之间的差距.
  • 这种方法促进了先进的分析,如空间RNA速度推断和in-silico扰动研究.
  • 维斯塔增强了空间和内在细胞变异的分解,改善了从空间转录组学获得的生物见解.