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相关概念视频

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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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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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.
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Genomics02:02

Genomics

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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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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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DNA as a Genetic Template02:05

DNA as a Genetic Template

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Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...
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DNA-Tethered RNA Polymerase for Programmable In vitro Transcription and Molecular Computation
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DNA计算:DNA电路和数据存储.

Hang Xu1, Yifan Yu1, Peixin Li1

  • 1College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Science, National Laboratory of Solid State Microstructures, Jiangsu Key Laboratory of Artificial Functional Materials, Chemistry and Biomedicine Innovation Center, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210023, China. ytian@nju.edu.cn.

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概括
此摘要是机器生成的。

DNA计算提供了一种新的计算方法,利用分子反应实现高平行性,高效的存储和低能耗. 这项技术有望解决传统计算机无法解决的复杂问题.

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科学领域:

  • 生物技术是生物技术.
  • 计算机科学 计算机科学
  • 计算生物学 计算生物学

背景情况:

  • 计算对社会发展至关重要,其体积,速度和准确性是关键因素.
  • 传统的计算方法在处理某些复杂问题时面临局限性.
  • 量子,光子和DNA计算等新兴技术旨在克服这些局限性.

研究的目的:

  • 为提供DNA计算理论基础的概述.
  • 要突出DNA计算对传统方法的优势.
  • 评估DNA计算的当前发展和未来潜力.

主要方法:

  • 审查DNA计算的理论基础.
  • 分析DNA计算的优点:高并行性,高效的存储和低能耗.
  • 评估目前DNA电路和DNA信息存储方面的发展.

主要成果:

  • DNA计算利用自发的DNA反应进行计算,使得高平行度成为可能.
  • 与传统计算相比,它提供了显著的优势,包括高效的数据存储和降低能耗.
  • DNA计算特别适合解决复杂的问题,包括NP难题.

结论:

  • DNA计算提供了一个独特而强大的计算模型.
  • 它的固有优势使它成为高复杂度计算挑战的可行解决方案.
  • 进一步开发DNA电路和信息存储将推动DNA计算的未来.