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相关概念视频

Next-generation Sequencing03:00

Next-generation Sequencing

88.5K
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....
88.5K
Sanger Sequencing01:57

Sanger Sequencing

753.9K
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...
753.9K
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

11.1K
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...
11.1K
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...
36.2K
RNA-seq03:21

RNA-seq

9.9K
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...
9.9K
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

18.8K
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: Jun 17, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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机器学习赋权下一代DNA测序:视角和招股说明书

Sneha Mittal1, Milan Kumar Jena1, Biswarup Pathak1

  • 1Department of Chemistry, Indian Institute of Technology (IIT) Indore Indore Madhya Pradesh 453552 India biswarup@iiti.ac.in.

Chemical science
|August 9, 2024
PubMed
概括

机器学习 (ML) 为超快速,低成本,准确的DNA测序提供了一个有前途的方法. 本框架探讨了机器学习辅助下一代测序,突出了人工智能在基因组学中的机遇和挑战.

科学领域:

  • 基因组学和生物信息学
  • 纳米技术 纳米技术
  • 个性化医疗是个性化的医疗.

背景情况:

  • 对快速,负担得起和精确的DNA测序的需求对于推进个性化医学的发展至关重要.
  • 机器学习 (ML) 算法已经在包括纳米科学在内的各种科学领域显示出显著的潜力.
  • 目前ML在DNA测序中的应用还处于起步阶段,但对高吞吐量分析具有前景.

研究的目的:

  • 为 ML 辅助下一代 DNA 测序提供一个全面的框架.
  • 引导人工智能驱动的DNA测序技术的发展.
  • 探索ML增强DNA测序的当前环境,机遇和挑战.

主要方法:

  • 审查适用于DNA测序的最新ML算法.
  • 整合领域知识与ML方法,以提高测序准确度.
  • 分析由DNA测序生成的复杂数据集.

主要成果:

  • 机器学习算法有可能破译DNA测序数据中的复杂模式.
  • 提出了一个整体的框架,整合了ML和领域知识.
  • 识别了ML辅助DNA测序领域的关键机遇和挑战.

更多相关视频

Collection and Extraction of Saliva DNA for Next Generation Sequencing
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Collection and Extraction of Saliva DNA for Next Generation Sequencing

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Targeted DNA Methylation Analysis by Next-generation Sequencing

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相关实验视频

Last Updated: Jun 17, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

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Collection and Extraction of Saliva DNA for Next Generation Sequencing
06:58

Collection and Extraction of Saliva DNA for Next Generation Sequencing

Published on: August 27, 2014

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Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

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结论:

  • 机器学习具有巨大的潜力,可以彻底改变DNA测序,使得结果更快,更准确.
  • 需要进一步的研究和开发来克服挑战,并充分实现AI在基因组学方面的能力.
  • 解决关键问题对于人工智能DNA测序器的发展至关重要.