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RNA-seq03:21

RNA-seq

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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...
9.8K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
7.0K
Genetic Screens02:46

Genetic Screens

4.9K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
4.9K
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
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Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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  1. 首页
  2. Levseq:用于定向进化和机器学习的快速生成序列函数数据.
  1. 首页
  2. Levseq:用于定向进化和机器学习的快速生成序列函数数据.

相关实验视频

Directed Evolution Method in Saccharomyces cerevisiae: Mutant Library Creation and Screening
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Directed Evolution Method in Saccharomyces cerevisiae: Mutant Library Creation and Screening

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LevSeq:用于定向进化和机器学习的快速生成序列函数数据.

Yueming Long1, Ariane Mora1, Francesca-Zhoufan Li2

  • 1Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California91125, United States.

ACS synthetic biology
|December 24, 2024

在PubMed 上查看摘要

概括
此摘要是机器生成的。

我们开发了Long-read every variant Sequencing (LevSeq) 技术,以快速生成蛋白质序列功能数据. 这种方法通过改善图书馆质量控制来帮助数据驱动的蛋白质工程和机器学习引导的蛋白质工程 (MLPE).

关键词:
定向进化的指导进化机器学习 机器学习变种 图书馆 图书馆纳米孔测序的测序蛋白质工程是指蛋白质工程.序列函数数据 序列函数数据

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科学领域:

  • 生物化学 生物化学
  • 分子生物学分子生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 序列功能数据对于理解蛋白质格局至关重要,但在定向进化过程中很少产生.
  • 获取综合序列函数数据的现有方法通常是耗时和资源密集的.

研究的目的:

  • 引入长读每种变异测序 (LevSeq),这是一个用于快速生成蛋白质序列功能数据的新管道.
  • 为了实现数据驱动的蛋白质工程和机器学习引导的蛋白质工程 (MLPE).

主要方法:

  • LevSeq使用双条码策略与纳米孔测序相结合.
  • 该管道无地集成到现有的蛋白质工程工作流程中.
  • 为数据分析和可视化提供开源软件.

主要成果:

  • LevSeq可以快速生成整个蛋白质编码基因的序列功能数据.
  • 该方法有助于对突变发生库的质量控制,降低成本和时间.
  • 模拟研究证实了LevSeq在各种条件下对变种检测的准确性.
  • LevSeq在新化学工程中证明了原蛋白质的实用性.

结论:

  • LevSeq通过提供必要的序列功能数据,使数据驱动的蛋白质工程成为可能.
  • 广泛采用和数据共享将促进对蛋白质序列功能关系的理解.
  • 该管道提高了效率,并减少了蛋白质工程工作中的资源支出.