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

RNA-seq03:21

RNA-seq

10.0K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.0K
Leaky Scanning02:28

Leaky Scanning

5.1K
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...
5.1K
RNA Splicing01:32

RNA Splicing

56.4K
Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...
56.4K
Ribosome Profiling02:24

Ribosome Profiling

3.5K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.5K
Chromatin Structure and RNA Splicing02:41

Chromatin Structure and RNA Splicing

2.7K
2.7K
RNA Interference01:23

RNA Interference

26.0K
RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
26.0K

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

Intelligent mobile health management for the risk of gastrointestinal bleeding in anticoagulated patients with cardiovascular disease.

Revista da Escola de Enfermagem da U S P·2026
Same author

GraphLooper: predicting chromatin loops based on hierarchical multi-view graph pooling method.

Briefings in bioinformatics·2026
Same author

MambaSSM: efficient segmentation of brain structures in anisotropic 3D EM images via state-space models.

Frontiers in neuroscience·2026
Same author

Tumor control probability modeling of stereotactic radiosurgery and fractionated stereotactic radiosurgery for patients with brainstem metastases.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2026
Same author

A scalable computational framework for predicting gene expression from candidate <i>cis</i>-regulatory elements.

Genome research·2026
Same author

Effect of Longgu on prognostic survival and nutritional status of critically ill patients with incontinence-associated dermatitis.

Pakistan journal of pharmaceutical sciences·2025
Same journal

Covariance decomposition for distance based species tree estimation.

BMC bioinformatics·2026
Same journal

SNPio: a Python interface for population genomic data processing.

BMC bioinformatics·2026
Same journal

SpaHNR: a spatial domain identification method via sparse attention-based hierarchical node representation and multi-view contrastive learning.

BMC bioinformatics·2026
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
查看所有相关文章

相关实验视频

Updated: Jul 8, 2025

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
07:35

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

697

scInterpreter:一个知识规范化的生成模型,用于可解释地集成scRNA-seq数据.

Zhen-Hao Guo1,2, Yan Wu3, Siguo Wang4

  • 1College of Electronics and Information Engineering, Tongji University, Shanghai, 200000, China.

BMC bioinformatics
|December 16, 2023
PubMed
概括
此摘要是机器生成的。

scInterpreter是一个新的深度学习工具,使单细胞RNA测序数据分析更加可解释和高效. 它的性能优于现有的方法,并揭示了生物学上重要的细胞表征.

关键词:
批量纠正批量纠正深度学习是一种深度学习.整合 整合 整合知识规范化的知识.一个单细胞RNA-seqq.

更多相关视频

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
09:58

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Published on: December 9, 2016

13.7K
Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

3.5K

相关实验视频

Last Updated: Jul 8, 2025

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
07:35

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

697
Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
09:58

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Published on: December 9, 2016

13.7K
Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

3.5K

科学领域:

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

背景情况:

  • 单细胞RNA测序 (scRNA-seq) 数据通过整合分析为生物发现提供了巨大的潜力.
  • 当前的整合模型往往缺乏解释性,并且很难训练,限制了它们的广泛应用.

研究的目的:

  • 为scRNA-seq数据集成开发一种可解释和高效的深度学习模型.
  • 解决现有的黑子集成方法的局限性.

主要方法:

  • 提出了scInterpreter,这是一个基于深度学习的可解释模型,用于scRNA-seq数据集成.
  • 对scInterpreter的性能与基准数据集上的最新模型进行了评估.
  • 评估模型的可扩展性,以集成和注释 atlas scRNA-seq 数据.
  • 研究了知识先验对加速培训过程的影响.
  • 在嵌入空间中对细胞表示进行了可解释性分析.

主要成果:

  • 在多个基准数据集中,scInterpreter显著超过了现有的最先进模型.
  • 该模型在各种评估场景中显示出强度.
  • 纳入先前的知识显著加快了培训过程.
  • 解释性分析显示,细胞表征捕获了重要的生物意义,在PBMC数据中识别了与特定途径相关的新型基因.

结论:

  • scInterpreter是scRNA-seq数据集成的有效和可解释的工具.
  • 该模型的细胞表示具有生物学意义,有助于途径和基因发现.
  • 预计scInterpreter将极大地促进单细胞转录组学研究.