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相关概念视频

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...
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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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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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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...
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Gene Duplication and Divergence02:37

Gene Duplication and Divergence

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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.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are...
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What is Gene Expression?01:42

What is Gene Expression?

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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
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RNA-seq03:21

RNA-seq

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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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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相关实验视频

Updated: May 16, 2025

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.

bioRxiv : the preprint server for biology
|April 1, 2025
PubMed
概括
此摘要是机器生成的。

维斯塔可以预测空间转录组学数据中的基因表达,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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Visualizing Genetic Variants, Short Targets, and Point Mutations in the Morphological Tissue Context with an RNA In Situ Hybridization Assay
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Visualizing Genetic Variants, Short Targets, and Point Mutations in the Morphological Tissue Context with an RNA In Situ Hybridization Assay

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相关实验视频

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科学领域:

  • 基因组学就是基因组学.
  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 在空间背景下了解细胞活动对于破译组织功能至关重要.
  • 单细胞RNA测序 (scRNA-seq) 提供了细胞水平的基因表达,但缺乏空间信息.
  • 亚细胞空间转录组学 (SST) 提供高分辨率的空间基因表达,但描述了一个有限的基因组.

研究的目的:

  • 介绍VISTA,一种新的计算方法,用于预测空间转录组学数据中的未观察到的基因表达.
  • 通过实现全面的基因分析来增强SST数据的实用性.
  • 为了更深入地了解空间解析的细胞状态和功能.

主要方法:

  • 维斯塔采用变异推断和几何深度学习,共同建模scRNA-seq和SST数据.
  • 该方法结合了不确定性量化,以进行可靠的预测.
  • 该方法旨在有效分析大规模空间转录组学数据集.

主要成果:

  • 与现有方法相比,VISTA在基因表达赋值方面表现出优异的性能.
  • 该方法显示,对于大型数据集,时间效率和内存消耗都令人满意.
  • 输入的基因表达数据使各种下游分析成为可能.

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.
  • 该方法为空间转录组学分析打开了新的可能性,包括识别空间变量的基因和联体受体相互作用.
  • 维斯塔 (VISTA) 通过提供更全面的组织内基因活性视图,推进空间生物学研究.