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相关概念视频

DNA Microarrays02:34

DNA Microarrays

17.1K
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...
17.1K
Gene Duplication and Divergence02:37

Gene Duplication and Divergence

6.0K
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...
6.0K
Improving Translational Accuracy02:07

Improving Translational Accuracy

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2.5K
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...
9.8K
Ribosome Profiling02:24

Ribosome Profiling

3.4K
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...
3.4K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.3K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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相关实验视频

Updated: May 24, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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跨空间转录组学平台的基因表达的联合归算和解卷.

Hongyu Zheng1, Hirak Sarkar1,2, Benjamin J Raphael1

  • 1Department of Computer Science, Princeton University, Princeton, NJ, USA.

bioRxiv : the preprint server for biology
|March 3, 2025
PubMed
概括

计算和解卷空间集成 (SIID) 集成来自多个空间解析的转录组学 (SRT) 技术的数据. 这种新的算法准确地归因于缺失的基因表达,并从混合数据中解构细胞类型,改进空间转录学分析.

科学领域:

  • 空间转录组学 空间转录组学
  • 计算生物学是一种计算生物学.
  • 基因组学就是基因组学.

背景情况:

  • 空间分辨率转录组学 (SRT) 技术为各种分辨率的组织基因表达提供了洞察力.
  • 现有的SRT平台在空间分辨率,基因覆盖和测序深度方面各不相同.
  • 整合来自不同SRT技术的数据可以克服单个平台的限制.

研究的目的:

  • 引入空间整合用于推算和解卷 (SIID),用于重建空间基因表达矩阵的算法.
  • 为了能够从配对的SRT数据中归算未测量的基因和细胞类型的解卷.
  • 为增强空间转录学数据分析提供计算工具.

主要方法:

  • SIID使用空间对齐和联合非负因子模型.
  • 该算法从配对的SRT观测结果中重建了一个潜在的空间基因表达矩阵.
  • SIID的PyTorch实现是公开可用的.

主要成果:

  • SIID在模拟点对细胞类型分配和基因表达恢复方面表现出卓越的性能.
  • 该算法准确地将缺失的基因表达数据归因于配对的SRT数据集.
  • 在现实世界的应用中,SIID在从Xenium-Visium数据中赋予持久基因表达的高性能.

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相关实验视频

Last Updated: May 24, 2025

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结论:

  • SIID有效地整合了来自不同SRT技术的数据,以克服局限性.
  • 该算法提高了基因表达归算和细胞类型解卷的准确性.
  • SIID提供了一个强大的工具,用于推进癌症组织及其他领域的空间转录学研究.