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相关概念视频

2D NMR: Overview of Heteronuclear Correlation Techniques01:18

2D NMR: Overview of Heteronuclear Correlation Techniques

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Heteronuclear correlation spectroscopy is an analytical technique that investigates the coupling between different types of nuclei, often a proton and an X-nucleus, such as carbon-13 or nitrogen-15. This method is commonly used in nuclear magnetic resonance (NMR) spectroscopy to gain insights into complex chemical compounds' structural and compositional aspects. A typical heteronuclear correlation spectrum displays X-nucleus chemical shifts on one axis and a proton spectrum on the other...
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2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

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Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
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2D NMR: Homonuclear Correlation Spectroscopy (COSY)01:06

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Homonuclear correlation spectroscopy, or COSY, is a 2-dimensional NMR technique that provides information about coupled protons. Typically, the geminal and vicinal coupling are observed. For example, consider the COSY spectrum of ethyl acetate, where its 1D proton NMR spectrum is plotted along the vertical and horizontal axes with their corresponding chemical shift scale. Three spots on the diagonal corresponding to the three peaks in the 1D proton spectrum are called diagonal peaks. The COSY...
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Proteomics01:33

Proteomics

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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...
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.
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通过和持久同质学测试omics数据.

Davide Gurnari1, Aldo Guzmán-Sáenz2, Filippo Utro2

  • 1Dioscuri Centre in Topological Data Analysis, Mathematical Institute PAN, Warsaw, Poland.

Scientific reports
|November 6, 2025
PubMed
概括
此摘要是机器生成的。

使用和持久同质的拓数据分析 (TDA) 可以识别复杂疾病中的分子生物标志物. 这种方法揭示了多omics数据中的隐藏模式,用于疾病亚型和生物标志物发现.

关键词:
数据分析数据分析多个omics的多个omics.发现模式的发现.拓学数据分析的分析.

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科学领域:

  • 计算生物学 计算生物学
  • 数据科学数据科学数据科学
  • 基因组学就是基因组学.

背景情况:

  • 在复杂疾病中识别分子签名,从高维多omics数据中识别具有类似症状的复杂疾病中的分子签名是具有挑战性的.
  • 拓数据分析 (TDA) 提供了一种几何方法,可以从数据中提取高阶关系.

研究的目的:

  • 将和持久同质性应用于多omics数据,以改进生物标记物识别.
  • 为了克服对同类类的TDA内周期表示的局限性.

主要方法:

  • 在多omics数据集上使用了和持久同质学,TDA技术.
  • 应用该方法来分析高维数据的几何结构.

主要成果:

  • 发现隐藏的模式和不同欧米特征之间的关系.
  • 在癌症数据中成功识别了预测疾病亚型的生物标志物.
  • 证明了用于生物标志物发现的多omics数据的有效剖析.

结论:

  • 波持久同理学对于多omics数据分析是有效的.
  • 这种方法有助于疾病亚型和识别复杂疾病的生物标志物.
  • 该方法突出了与疾病相关的潜在生物途径.