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相关概念视频

What is Gene Expression?01:36

What is Gene Expression?

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A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
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Ribosome Profiling02:24

Ribosome Profiling

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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...
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Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Conserved Binding Sites01:49

Conserved Binding Sites

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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mRNA Stability and Gene Expression02:51

mRNA Stability and Gene Expression

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Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

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Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
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相关实验视频

Updated: Jun 3, 2025

An Integrated Approach for Microprotein Identification and Sequence Analysis
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从蛋白质序列进行有效的基因表达预测和优化.

Tuoyu Liu1,2,3, Yiyang Zhang2, Yanjun Li2

  • 1State Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|January 9, 2025
PubMed
概括
此摘要是机器生成的。

这项研究揭示了蛋白质序列和表达之间的联系,开发了SRAB和AEI指标. 一个新的AI模型准确地预测了88个物种的蛋白质表达,从而实现了优化基因表达和突变设计.

关键词:
氨基酸表达指数指数突变的世代是突变的一代.预测蛋白质表达的时间可溶性表达的可溶性表达转移学习转移学习

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

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相关实验视频

Last Updated: Jun 3, 2025

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科学领域:

  • 生物技术是生物技术.
  • 蛋白质工程是指蛋白质工程.
  • 计算生物学 计算生物学

背景情况:

  • 在异质系统中,高可溶性蛋白质表达对于研究和应用至关重要.
  • 蛋白质序列对表达水平的影响通常被低估,而不是与代码的使用相比.

研究的目的:

  • 揭示蛋白质序列与异质宿主中可溶性表达之间的关系.
  • 根据序列特征开发优化蛋白质表达的预测模型.

主要方法:

  • 开发SRAB (相对氨基酸偏差的强度) 和AEI (氨基酸表达指数) 以量化序列表达相关性.
  • 微调MP-TRANS (MindSpore Protein Transformer) 模型以创建88个MPB-EXP模型,用于预测88个物种的表达.
  • 使用MPB-MUT模型生成表达增强突变物.

主要成果:

  • AEI指标显示出与可溶性蛋白质表达的正相关性.
  • MPB-EXP模型的平均预测准确度为0.78,超过了传统的机器学习方法.
  • 实验验证证证实了先前未表达的西兰酶突变体在大肠杆菌中的成功高水平可溶性表达.

结论:

  • 蛋白质序列是异质蛋白质表达的重要决定因素.
  • 开发的AI模型为预测和优化蛋白质表达提供了强大的工具.
  • 这种方法促进了在特定宿主中增强表达的蛋白质的设计.