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

Proteomics01:33

Proteomics

7.4K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.4K
Ribosome Profiling02:24

Ribosome Profiling

3.6K
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...
3.6K
Protein Networks02:26

Protein Networks

4.0K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.0K
Methods of Classification and Identification01:28

Methods of Classification and Identification

37
Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
37
RNA-seq03:21

RNA-seq

10.1K
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...
10.1K
MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

4.9K
Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.
Matrix-assisted laser desorption ionization (MALDI) is a commonly...
4.9K

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

Interpretable prediction and generation of ASC-speck aptamers using multiscale deep biological learning models.

Bioinformatics advances·2026
Same author

scRADAR: Dissecting intratumoral drug response heterogeneity at single-cell resolution via mechanism-guided prototype routing.

PLoS computational biology·2026
Same author

RPI-PLMGNN: Enhancing RNA-Protein Interaction Prediction with the Pretrained Large Language Models and Graph Neural Networks.

ACS synthetic biology·2026
Same author

MPMFMol: Multitask Self-Supervised Pretraining with Multimodal Fine-Tuning for Molecular Property Prediction.

Journal of chemical information and modeling·2026
Same author

Quantum computing applications in drug discovery.

Briefings in bioinformatics·2026
Same author

MuFGPS: enhancing liquid-liquid phase separation protein prediction through multi-level features and ensemble learning.

Briefings in bioinformatics·2026

相关实验视频

Updated: Jul 21, 2025

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.4K

特殊蛋白质或RNA分子 计算识别 特殊蛋白质或RNA分子

Ren Qi1,2, Quan Zou1,3

  • 1Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324000, China.

International journal of molecular sciences
|July 29, 2023
PubMed
概括

计算方法对于识别特殊的蛋白质和RNA分子至关重要. 这有助于理解生物功能和开发新型疾病治疗方法.

更多相关视频

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions
10:52

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Published on: September 28, 2017

8.2K
mRNA Interactome Capture from Plant Protoplasts
12:29

mRNA Interactome Capture from Plant Protoplasts

Published on: July 28, 2017

9.2K

相关实验视频

Last Updated: Jul 21, 2025

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.4K
Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions
10:52

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Published on: September 28, 2017

8.2K
mRNA Interactome Capture from Plant Protoplasts
12:29

mRNA Interactome Capture from Plant Protoplasts

Published on: July 28, 2017

9.2K

科学领域:

  • 生物化学和分子生物学
  • 生物信息学和计算生物学

背景情况:

  • 识别特定的蛋白质和RNA分子对于生物研究至关重要.
  • 计算方法为分子识别提供了强大的工具.

研究的目的:

  • 突出计算方法在识别关键蛋白质和RNA分子中的重要性.
  • 强调这些识别在推进疾病治疗策略中的作用.

主要方法:

  • 利用计算算法进行分子分析.
  • 使用生物信息学工具进行数据处理和解释.

主要成果:

  • 证明了计算方法在确定重要的生物分子中的有效性.
  • 建立了分子识别和潜在的治疗开发之间的联系.

结论:

  • 对蛋白质和RNA的计算识别对于生物学理解至关重要.
  • 这种方法加速了针对各种疾病的新型治疗干预措施的开发.