Jove
Visualize
联系我们

相关概念视频

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

18.7K
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.
18.7K
DNA as a Genetic Template02:05

DNA as a Genetic Template

21.5K
Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...
21.5K
Genomics02:02

Genomics

35.3K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
35.3K
Genetic Lingo01:11

Genetic Lingo

98.6K
Overview
98.6K
Leaky Scanning02:28

Leaky Scanning

5.0K
During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
5.0K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.6K
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...
5.6K

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

Navigating the Multiverse: a Hitchhiker's guide to selecting harmonization methods for multimodal biomedical data.

Biology methods & protocols·2025
Same author

Uncovering co-regulatory modules and gene regulatory networks in the heart through machine learning-based analysis of large-scale epigenomic data.

Computers in biology and medicine·2024
Same author

Integrative omics identifies conserved and pathogen-specific responses of sepsis-causing bacteria.

Nature communications·2023
Same author

Transcriptomic analysis reveals myometrial topologically associated domains linked to the onset of human term labour.

Molecular human reproduction·2022
Same author

A Survey of Current Resources to Study lncRNA-Protein Interactions.

Non-coding RNA·2021
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

相关实验视频

Updated: May 17, 2025

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

9.6K

基因组语言建模 (GLM):一个初学者的作弊表.

Navya Tyagi1,2, Naima Vahab3, Sonika Tyagi3

  • 1AI and Data Science, Indian Institute of Technology, Madras, Chennai 600036, Tamil Nadu, India.

Biology methods & protocols
|May 15, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了基因组语言建模 (GLM) 以将基因组数据凝结为个性化医学的可解释特征. 它提供了一个使用机器学习将基因组序列转化为生物学上有意义的信息的指南.

关键词:
在这里,我们可以看到AIAIAI.数字健康数字健康基因组学就是基因组学.机器学习是机器学习.自然语言处理自然语言处理.精准医学是一门精准医学.

更多相关视频

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project
10:19

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

17.3K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

614

相关实验视频

Last Updated: May 17, 2025

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

9.6K
Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project
10:19

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

17.3K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

614

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:

  • 将各种数据模式与基因组学相结合,是个性化医学的关键.
  • 基因组数据的大小和独特的结构带来了重大整合挑战.
  • 为了与其他数据类型的互操作性,需要缩小基因组表示.

研究的目的:

  • 探索传统和最先进的基因组语言建模 (GLM) 方法.
  • 为机器学习提供关于从基因组序列中表示和提取特征的指南.
  • 讨论机器学习在基因组学和多式联络集成中的应用.

主要方法:

  • 基因组序列预处理和令牌化技术.
  • 特性提取方法包括频率,嵌入和基于神经网络的方法.
  • 在基因组序列数据上应用语言建模.

主要成果:

  • 证明有效的特征提取用于分析大型基因组数据集.
  • 突出了GLM在功能注释和数据解释中的作用.
  • 展示了先进的ML模型,如BERT,用于增强基因组数据分析.

结论:

  • GLM提供了一种新的方法,将复杂的基因组数据转化为生物可解释的信息.
  • 本指南有助于在基因组学中开发数据驱动的假设.
  • 有效的特征提取对于多式基因组框架中的机器学习至关重要.