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

Improving Translational Accuracy02:07

Improving Translational Accuracy

2.5K
2.5K
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
Transfer RNA Synthesis02:35

Transfer RNA Synthesis

2.8K
2.8K
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.2K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.2K
Protein Complex Assembly02:41

Protein Complex Assembly

2.0K
2.0K
Alternative RNA Splicing02:18

Alternative RNA Splicing

3.7K
3.7K

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

Associations between twelve composite inflammatory indices and sarcopenia in a health examination population: a cross-sectional study.

Frontiers in public health·2026
Same author

Identifying key predictors of post-stroke depression and cognitive impairment in acute stroke survivors.

Frontiers in neurology·2026
Same author

From nutrient-based to food-based assessment: the evolution of inflammatory indices and their significance for metabolic syndrome and type 3 diabetes mellitus.

Frontiers in nutrition·2026
Same author

Evaluation of dosimetric consistency between pre- and postoperative CT-guided noncoplanar template-assisted ¹²⁵I seed implantation in recurrent and metastatic thoracic tumors: a retrospective study.

PeerJ·2026
Same author

Investigating the association between the food inflammation scores of individuals and stroke in adults: an extreme gradient boosting machine learning model interpreted with shapley additive explanations.

Journal of health, population, and nutrition·2026
Same author

Data-driven AI system for learning how to run transcript assemblers.

Genome biology·2026
Same journal

Layered social competition coordinates reproductive hierarchy formation in ants.

bioRxiv : the preprint server for biology·2026
Same journal

Combination epigenetic-targeted therapy increases the immunogenicity of poorly immunogenic sarcomas.

bioRxiv : the preprint server for biology·2026
Same journal

Loss of LanC-like proteins delays post-injury regeneration of aging skeletal muscles.

bioRxiv : the preprint server for biology·2026
Same journal

Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.

bioRxiv : the preprint server for biology·2026
Same journal

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy.

bioRxiv : the preprint server for biology·2026
Same journal

Sequence-encoded autoinhibition couples mRNA decapping activity to phase separation.

bioRxiv : the preprint server for biology·2026
查看所有相关文章

相关实验视频

Updated: Jun 7, 2025

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

2.2K

数据驱动的人工智能系统用于学习如何运行转录汇编器.

Yihang Shen1, Zhiwen Yan1, Carl Kingsford1

  • 1Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA.

bioRxiv : the preprint server for biology
|November 18, 2024
PubMed
概括
此摘要是机器生成的。

一个人工智能系统AutoTuneX优化了RNA-seq数据的转录组装参数. 它在98%的样本中提高了准确性,显著提高了从测序读取的转录重建.

更多相关视频

Automated Robotic Liquid Handling Assembly of Modular DNA Devices
11:22

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

12.3K
An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus
12:10

An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus

Published on: November 30, 2014

13.3K

相关实验视频

Last Updated: Jun 7, 2025

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

2.2K
Automated Robotic Liquid Handling Assembly of Modular DNA Devices
11:22

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

12.3K
An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus
12:10

An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus

Published on: November 30, 2014

13.3K

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:

  • RNA测序 (RNA-seq) 对于理解基因表达至关重要.
  • 转录汇编器重建表达的转录,但需要最佳的参数设置.
  • 手动调整参数是耗时的,可能不会产生最佳结果.

研究的目的:

  • 介绍AutoTuneX,这是一个人工智能驱动的系统,用于自动优化转录汇编器参数.
  • 为了提高从RNA-seq数据的转录组装的准确性和效率.
  • 在序列分析工具中提供数据驱动的参数选择策略.

主要方法:

  • 开发了AutoTuneX,这是一个机器学习系统,利用现有RNA-seq样本的知识.
  • 训练有素的AutoTuneX可以预测转录汇编器的最佳参数.
  • 在使用两个不同的转录组装器对1588个人类RNA-seq样本进行了AutoTuneX的评估.

主要成果:

  • 在98%的测试样本中,AutoTuneX预测了导致更准确的转录组装的参数.
  • 在曲线下面积 (AUC) 中观察到显著改善,一些病例达到600%的增强.
  • 该系统展示了有效的知识转移,以优化未见的RNA-seq样本的参数.

结论:

  • AutoTuneX提供了一个强大的,数据驱动的方法,可以自动优化转录汇编器参数.
  • 与默认设置相比,该系统大大提高了转录组装的准确性.
  • AutoTuneX代表了一种用于优化生物信息学工具在序列分析中的性能的新策略.