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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
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...
5.7K
Multiple Comparison Tests01:13

Multiple Comparison Tests

3.9K
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
3.9K
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

3.9K
Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
3.9K
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

107
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
107
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

73
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
73
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

204
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
204

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相关实验视频

Updated: Jun 15, 2025

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
07:49

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

7.0K

改进了使用SEEKR进行非线性序列比较的功能.

Shuang Li1,2,3, Quinn E Eberhard1,2,3,4, Luke Ni5

  • 1Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina 27599, USA.

RNA (New York, N.Y.)
|August 26, 2024
PubMed
概括
此摘要是机器生成的。

通过k-mer表示 (SEEKR) 的序列评估现在估计核酸序列相似性的统计意义. 新的SEEKR功能有助于识别功能性RNA元素和理解RNA-seq数据.

关键词:
XIST XIST 这是一个很好的例子.eCLIP eCLIP 是一个这里是K-MER.在ncRNA中,我们可以序列比较 序列比较

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Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
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Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

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Novel Sequence Discovery by Subtractive Genomics
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Novel Sequence Discovery by Subtractive Genomics

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相关实验视频

Last Updated: Jun 15, 2025

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

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Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
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Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

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Novel Sequence Discovery by Subtractive Genomics
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Novel Sequence Discovery by Subtractive Genomics

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科学领域:

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

背景情况:

  • 序列比较对于理解核酸功能至关重要.
  • 非线性相似性量化需要超越传统对齐的先进方法.
  • 长非编码RNAs (lncRNAs) 在序列分析中提出了独特的挑战.

研究的目的:

  • 引入SEEKR方法的增强功能,使统计学意义估计和k-mer相似性的可视化成为可能.
  • 展示SEEKR在识别特定的lncRNA特征和功能域中的应用.
  • 为利用SEEKR在lncRNA研究中提供指导方针,包括保存研究和注释验证.

主要方法:

  • 在SEEKR中开发新的统计功能,用于P值估计.
  • 实现用于k-mer相似性分析的可视化工具.
  • 应用SEEKR来识别具有XIST类特征的染色质丰富 lncRNA.
  • 对lncRNA片段的分析,以预测RNA-蛋白相互作用域.
  • 使用RNA-seq读数密度可视化为lncRNA注释支持.

主要成果:

  • 现在,SEEKR可以提供统计学上显著的序列相似度指标.
  • 确定了具有XIST类序列特征的新型染色质丰富lncRNAs.
  • 预测了 lncRNA 片段内潜在的 RNA-蛋白相互作用域.
  • 证明了SEEKR在评估lncRNA保存和验证注释方面的实用性.

结论:

  • 增强的SEEKR方法提供了对核酸序列相似性的可靠统计评估.
  • SEEKR促进了lncRNAs的发现和功能表征.
  • 将SEEKR与RNA-seq数据分析集成的最佳实践提高了lncRNA研究的可靠性.