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

The Central Dogma01:25

The Central Dogma

126.7K
Overview
126.7K
From DNA to Protein03:06

From DNA to Protein

18.5K
The flow of genetic information in cells from DNA to mRNA to protein is described by the central dogma, which states that genes specify the sequence of mRNAs, which in turn specify the sequence of amino acids making up all proteins. The decoding of one molecule to another is performed by specific proteins and RNAs. Because the information stored in DNA is so central to cellular function, it makes intuitive sense that the cell would make mRNA copies of this information for protein synthesis...
18.5K
Proteins: From Genes to Degradation02:11

Proteins: From Genes to Degradation

12.3K
Within a biological system, the DNA encodes the RNA, and the nucleotide sequence in the RNA further defines the amino acid sequence in the protein. This is referred to as “The Central Dogma of Molecular Biology” - a term coined by Francis Crick.  Central dogma is a firm principle in biology that defines the flow of genetic information within any life form. The two fundamental steps in central dogma are - transcription and translation.
Transcription is the synthesis of RNA...
12.3K
Translation01:31

Translation

142.1K
Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of...
142.1K
DNA as a Genetic Template02:05

DNA as a Genetic Template

22.0K
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...
22.0K
tRNA Activation02:26

tRNA Activation

19.3K
Aminoacyl-tRNA synthetases are present in both eukaryotes and bacteria. Though eukaryotes have 20 different aminoacyl-tRNA synthetases to couple to 20 amino acids, many bacteria do not have genes for all of these aminoacyl-tRNA synthetases. Despite this, they still use all 20 amino acids to synthesize their proteins. For instance, some bacteria do not have the gene encoding the enzyme that couples glutamine with its partner tRNA. In these organisms, one enzyme adds glutamic acid to all of the...
19.3K

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

Brain shuttle peptides derived from phage display.

Advances in pharmacology (San Diego, Calif.)·2026
Same author

Decoding and deciphering a subcellular ZIP code system.

Trends in cell biology·2026
Same author

Matrix Metalloproteinases as Candidate Antigenic Determinants for Anti-Tumor Autoantibodies in Human Ovarian Cancer: A Post Hoc Analysis.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology·2025
Same author

Human protein interactome structure prediction at scale with Boltz-2.

bioRxiv : the preprint server for biology·2025
Same author

From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning.

Structural dynamics (Melville, N.Y.)·2025
Same author

High-throughput prediction of peptide structural conformations with AlphaFold2.

bioRxiv : the preprint server for biology·2024

相关实验视频

Updated: Jul 13, 2025

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System
11:47

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System

Published on: August 1, 2016

16.0K

人工智能解释了中央教条和遗传代码.

Alexander M Ille1, Michael B Mathews2

  • 1School of Graduate Studies, Rutgers University, Newark, NJ, USA.

Trends in biochemical sciences
|October 13, 2023
PubMed
概括
此摘要是机器生成的。

生成型人工智能 (AI),特别是ChatGPT,可以定义分子生物学的中央教条并解释遗传密码,展示其在科学应用中的潜力.

关键词:
这是中央教条的核心教条.聊天GPT 聊天GPT 聊天序列假设 序列假设人工智能的人工智能是人工智能.大型语言模型.自然语言处理自然语言处理.

更多相关视频

Xenopus laevis as a Model to Identify Translation Impairment
10:24

Xenopus laevis as a Model to Identify Translation Impairment

Published on: September 27, 2015

10.8K
Optical Tweezers to Study RNA-Protein Interactions in Translation Regulation
12:26

Optical Tweezers to Study RNA-Protein Interactions in Translation Regulation

Published on: February 12, 2022

5.0K

相关实验视频

Last Updated: Jul 13, 2025

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System
11:47

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System

Published on: August 1, 2016

16.0K
Xenopus laevis as a Model to Identify Translation Impairment
10:24

Xenopus laevis as a Model to Identify Translation Impairment

Published on: September 27, 2015

10.8K
Optical Tweezers to Study RNA-Protein Interactions in Translation Regulation
12:26

Optical Tweezers to Study RNA-Protein Interactions in Translation Regulation

Published on: February 12, 2022

5.0K

科学领域:

  • 分子生物学分子生物学
  • 人工智能的人工智能

背景情况:

  • 生成型人工智能 (AI) 正在迅速发展,具有多样化的应用.
  • 人工智能融入科学研究带来了新的机遇和挑战.

研究的目的:

  • 评估聊天生成预训练变压器 (ChatGPT) 在理解核心生物概念方面的能力.
  • 评估ChatGPT在解释遗传密码方面的熟练程度.

主要方法:

  • 聊天GPT被要求定义分子生物学的中央教条.
  • 聊天GPT的任务是解释遗传密码.

主要成果:

  • 聊天GPT成功定义了分子生物学的中央教条.
  • 聊天GPT展示了一种解释遗传密码的能力.

结论:

  • 聊天GPT显示了协助科学理解和解释的潜力.
  • 需要进一步的研究来探索人工智能在分子生物学中的实用性的全部范围.