Jove
Visualize
联系我们

相关概念视频

DNA Microarrays02:34

DNA Microarrays

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...

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

Toxicity assessment of doxycycline-aided artificial intelligence-assisted drug design targeting candidate 16S rRNA methyltransferase gene.

BMC pharmacology & toxicology·2025
Same author

Atypical Presentation of Hepatitis A in Children.

Journal of the College of Physicians and Surgeons--Pakistan : JCPSP·2025
Same author

Effects of Machiavellianism on Cyberbullying Perpetration: Serial Mediating Role of Perceived Social Support and Problematic Internet Use Among University Students.

Psychology in Russia : state of the art·2025
Same author

Intimate Partner Violence and Postpartum Depression Among Pakistani Women: Moderating Role of Miscarriages.

Journal of interpersonal violence·2025
Same author

Optimizing IoT intrusion detection with cosine similarity based dataset balancing and hybrid deep learning.

Scientific reports·2025
Same author

Treadmill training protects valproic acid-induced autistic features via cerebellar AMPK/PPAR-γ dependent pathway and improves mitochondrial activity in mice.

Scientific reports·2025
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: Jul 4, 2026

Methylated RNA Immunoprecipitation Assay to Study m5C Modification in Arabidopsis
08:50

Methylated RNA Immunoprecipitation Assay to Study m5C Modification in Arabidopsis

Published on: May 14, 2020

6.7K

一个基于CNN的m5cRNA甲基化预测器.

Irum Aslam1, Sajid Shah2, Saima Jabeen3

  • 1Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, 22060, KPK, Pakistan.

Scientific reports
|December 11, 2023
PubMed
概括

本研究引入了一种1D CNN模型,以准确识别RNA m5c甲基化位点. 该模型有效地分析全长RNA序列,改进了用于检测RNA修饰的传统方法.

更多相关视频

Exploring m6A and m5C Epitranscriptomes upon Viral Infection: an Example with HIV
14:40

Exploring m6A and m5C Epitranscriptomes upon Viral Infection: an Example with HIV

Published on: March 5, 2022

3.3K
Author Spotlight: Decoding RNA Methylation's Role in Pancreatic Cancer - A Single-Base Resolution Study
06:57

Author Spotlight: Decoding RNA Methylation's Role in Pancreatic Cancer - A Single-Base Resolution Study

Published on: July 7, 2023

1.1K

相关实验视频

Last Updated: Jul 4, 2026

Methylated RNA Immunoprecipitation Assay to Study m5C Modification in Arabidopsis
08:50

Methylated RNA Immunoprecipitation Assay to Study m5C Modification in Arabidopsis

Published on: May 14, 2020

6.7K
Exploring m6A and m5C Epitranscriptomes upon Viral Infection: an Example with HIV
14:40

Exploring m6A and m5C Epitranscriptomes upon Viral Infection: an Example with HIV

Published on: March 5, 2022

3.3K
Author Spotlight: Decoding RNA Methylation's Role in Pancreatic Cancer - A Single-Base Resolution Study
06:57

Author Spotlight: Decoding RNA Methylation's Role in Pancreatic Cancer - A Single-Base Resolution Study

Published on: July 7, 2023

1.1K

科学领域:

  • 分子生物学分子生物学
  • 生物信息学是一种生物信息学.
  • 基因组学就是基因组学.

背景情况:

  • 转录后RNA修饰对于生物过程至关重要.
  • N6-甲基氨酸 (m6A) 和5-甲基氨酸 (m5c) 是影响基因表达的关键RNA修饰.
  • 实验检测m5c网站是劳动密集型和昂贵的.

研究的目的:

  • 开发一种有效的计算模型,用于识别RNA中的m5c甲基化位点.
  • 分析全长的RNA序列,不局限于中央动机.
  • 为了克服传统方法在处理高维RNA序列数据方面的局限性.

主要方法:

  • 采用了一个端到端,1D卷积神经网络 (CNN) 模型.
  • 该模型在预处理的RNA序列 (41个核酸) 和全长序列上进行了训练和评估.
  • 优化了特征提取技术,以直接处理RNA序列.

主要成果:

  • 拟议的1D CNN模型在分类m5c甲基化位点方面取得了高性能.
  • 对于41个核酸序列,获得了96.70%的灵敏度和96.21%的准确性.
  • 对于全长RNA序列的准确性达到了96.10%,超越了现有的方法.

结论:

  • 1D CNN模型为m5c站点识别提供了强大而准确的方法.
  • 该模型处理全长序列的能力提供了更全面的分析.
  • 这种计算方法通过减少实验负担,大大推进了RNA修饰研究.