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相关概念视频

Genetic Screens02:46

Genetic Screens

4.8K
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...
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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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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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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Genetic Lingo01:11

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Overview
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Sanger Sequencing01:57

Sanger Sequencing

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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相关实验视频

Updated: May 9, 2025

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

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使用ChatGPT作为培训非程序员生成基因组序列分析代码的工具.

Haley A Delcher1, Enas S Alsatari1, Adeyeye I Haastrup1

  • 1Department of Pharmacology, University of South Alabama, Mobile, Alabama, USA.

Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology
|May 5, 2025
PubMed
概括
此摘要是机器生成的。

没有编程技能的生物学学生现在可以使用ChatGPT分析大型下一代测序 (NGS) 数据集. 这种人工智能工具使他们能够生成自定义的Python代码,弥合生物学和计算机科学之间的差距,用于关键的基因组数据分析.

关键词:
积极学习是积极学习.计算生物学是计算生物学.在研究和教学中使用计算机.课程设计开发和实施课程设计和实施.基因组学 蛋白质组学 生物信息学研究的整合到本科教学.教学和学习的原始模型.

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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

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科学领域:

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

背景情况:

  • 对缺乏编程专业知识的生物学家来说,分析大型基因组数据集是一项挑战.
  • 这往往需要与计算机科学家的合作或广泛的个人培训.
  • 目前的局限性阻碍了生物研究中的独立基因组数据分析.

研究的目的:

  • 为了展示ChatGPT如何使没有编程背景的生物学学生能够分析大型下一代测序 (NGS) 数据集.
  • 将人工智能工具集成到本科研究课程中,以培养实际的生物信息技术技能.
  • 弥合生物学研究和计算分析能力之间的差距.

主要方法:

  • 在基于课程的本科研究经验 (CURE) 课程中实施ChatGPT.
  • 利用学生现有的生物学知识作为ChatGPT生成Python代码的提示.
  • 指导ChatGPT创建能够处理和分析大型NGS数据集 (>10 GB) 的程序.

主要成果:

  • 学生通过ChatGPT只使用生物学提示成功生成了Python程序.
  • 这些程序有效分析了超过10千兆字节的下一代测序数据集.
  • 这种方法使学生能够进行全面的,可发表的质量数据分析.

结论:

  • 在教育中整合ChatGPT可以为生物学家提供基因组数据分析的基本编程技能.
  • 像ChatGPT这样的AI工具可以弥合生物学和计算机科学之间的跨学科差距.
  • 聊天GPT为生物学研究人员提供了一个强大的新途径,以加速NGS数据分析和科学发现.