Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

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
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

18.8K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
18.8K
Nucleic Acid Structure01:25

Nucleic Acid Structure

6.1K
The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...
6.1K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

How FAIR is VIS?

IEEE computer graphics and applications·2025
Same author

MutationExplorer: a webserver for mutation of proteins and 3D visualization of energetic impacts.

Nucleic acids research·2024
Same author

MUTATIONEXPLORER- A WEBSERVER FOR MUTATION OF PROTEINS AND 3D VISUALIZATION OF ENERGETIC IMPACTS.

bioRxiv : the preprint server for biology·2024
Same author

MDsrv: visual sharing and analysis of molecular dynamics simulations.

Nucleic acids research·2022
Same author

An Interactive Decision Support System for Land Reuse Tasks.

IEEE computer graphics and applications·2022
Same author

Masakari: visualization supported statistical analysis of genome segmentations.

BMC bioinformatics·2020
Same journal

Hydrogen sulfide modulates gene networks in hypoxia/reoxygenation-stressed trophoblasts: insights from transcriptome profiling.

Frontiers in bioinformatics·2026
Same journal

Molecular Dynamics-Based validation of a quinazoline-based KRAS inhibitor (C9) identified through QSAR-guided discovery.

Frontiers in bioinformatics·2026
Same journal

Real-world chronic recordings from implantable adaptive deep brain stimulation systems for Parkinson's disease motor state classification.

Frontiers in bioinformatics·2026
Same journal

A foundational quantum framework for multi-pattern string matching in k-mer detection.

Frontiers in bioinformatics·2026
Same journal

Explainable machine learning-based identification of transcriptomic biomarkers in CD1c+ dendritic cells for non-infectious uveitis: an integrative analysis of bulk RNA-seq data.

Frontiers in bioinformatics·2026
Same journal

Polygenic modeling of genetic effects on both phenotypic mean and variance: distributional regression for BMI, blood and urine biomarkers in the UK Biobank.

Frontiers in bioinformatics·2026
查看所有相关文章

相关实验视频

Updated: Jun 14, 2025

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

10.4K

一个全基因组多重序列对齐图的布局框架.

Jeremias Schebera1,2, Dirk Zeckzer1, Daniel Wiegreffe1

  • 1Image and Signal Processing Group, Institute for Computer Science, Leipzig University, Leipzig, Germany.

Frontiers in bioinformatics
|September 2, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的图形绘制框架,以可视化基因组序列对齐,保持顺序上下文. 该框架有助于分析基因组结构变异和比较基因组学.

关键词:
基因组分析 基因组分析基因组比较 基因组比较图表绘制图表绘制图表绘制图表多个序列对齐的多重序列对齐.视觉化的可视化

更多相关视频

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

9.7K
A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.3K

相关实验视频

Last Updated: Jun 14, 2025

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

10.4K
Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

9.7K
A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.3K

科学领域:

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

背景情况:

  • 基因组数据分析通常依赖于序列对齐,通常在较小的间隔内进行.
  • 比较较长的序列需要将它们分成较小的间隔,导致失去原始序列顺序的上下文.
  • 现有的方法在对齐分析期间努力保持基因组的全球秩序和结构变异.

研究的目的:

  • 开发一个图形绘图框架来表示通用多重序列对齐 (gMSA) 数据.
  • 为了能够在半全球范围内可视化基因组顺序和结构变异.
  • 通过强调基于参考基因组的差异和相似之处来支持比较基因组分析.

主要方法:

  • 提出一个专门为gMSA数据设计的新的图形绘制框架.
  • 开发用于等级图表布局生成的算法.
  • 实现一个原型框架与示例数据集进行演示.

主要成果:

  • 为gMSA图表提供了一个完整的图形绘制框架.
  • 该框架为进行比较基因组分析生成分层布局.
  • 可视化有效地揭示了基因组顺序相对于参考的差异和相似之处.

结论:

  • 拟议的框架成功地使用图形结构来表示gMSA数据.
  • 层次图表布局为基因组结构变异提供了有价值的见解.
  • 该框架促进了半全球性比较基因组分析,并有助于理解基因组进化.