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相关概念视频

Genomics02:02

Genomics

36.2K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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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 Screens02:46

Genetic Screens

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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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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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The Central Dogma01:20

The Central Dogma

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The central dogma explains the flow of genetic information from DNA nucleotides to the amino acid sequence of proteins.
RNA is the Missing Link Between DNA and Proteins
In the early 1900s, scientists discovered that DNA stores all the information needed for cellular functions and that proteins perform most of these functions. However, the mechanisms of converting genetic information into functional proteins remained unknown for many years. Initially, it was believed that a single gene is...
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相关实验视频

Updated: Jun 13, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
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DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

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基因组学深度学习的进展

Yan-Chun Bao1,2, Cai-Xia Shi1, Chuan-Qiang Zhang3,4

  • 1College of Animal Science and Technology, Inner Mongolia Agricultural University, Hohhot 010018, China.

Yi chuan = Hereditas
|September 14, 2024
PubMed
概括
此摘要是机器生成的。

深度学习,一种人工智能技术,通过从高吞吐量测序中对大数据进行高级分析,正在彻底改变基因组学. 本综述探讨了其在DNA,RNA和蛋白质研究中的应用,提高了精度和效率.

关键词:
在美国,CNN是CNN.没有了,没有了,没有了.这是LSTM的LSTM.一个RNN RNN深度学习是一种深度学习.基因组 基因组是基因组的组成部分.

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A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
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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.
  • 人工智能的人工智能

背景情况:

  • 基因组学研究面临着由高通量测序产生的大数据带来的挑战.
  • 传统的生物信息学方法与复杂的基因组数据模式作斗争.
  • 深度学习为数据分析和模式识别提供先进的AI功能.

研究的目的:

  • 审查深度学习在基因组研究中的应用.
  • 探索四个主要的深度学习模型:CNN,RNN,LSTM和GAN.
  • 突出深度学习在牲畜基因组学中的作用,用于特征分析,疾病预防和遗传增强.

主要方法:

  • 对深度学习模型的审查 (CNN,RNN,LSTM,GAN).
  • 在过去五年中,对DNA,RNA和蛋白质研究中的应用进行分析.
  • 在牲畜基因组学中探索深度学习.

主要成果:

  • 深度学习模型在分析复杂的基因组数据方面显示出巨大潜力.
  • 应用范围跨越DNA,RNA和蛋白质研究,提高精度和效率.
  • 深度学习在牲畜基因组学中显示出对特征分析和育种的前景.

结论:

  • 深度学习是现代基因组学的转型技术.
  • 它提高了基因组研究和畜牧业的精度和效率.
  • 在畜牧基因组学中深度学习的框架开发对于推进育种技术至关重要.