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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
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

71
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
71
Predicting Products: Substitution vs. Elimination02:52

Predicting Products: Substitution vs. Elimination

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When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
11.4K
Exon Recombination02:32

Exon Recombination

3.5K
The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes. 
Exon shuffling follows “splice frame rules.” Each exon...
3.5K
Conservation of Protein Domains02:26

Conservation of Protein Domains

3.1K
3.1K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.0K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.0K

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相关实验视频

Updated: Jun 3, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

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一个无损的无引用序列压缩算法,利用语法,统计和替换规则.

Subhankar Roy1,2, Dilip Kumar Maity1, Anirban Mukhopadhyay2

  • 1Department of Computer Science & Engineering, Academy of Technology, Adisaptagram, Hooghly-712121, India.

Briefings in functional genomics
|January 8, 2025
PubMed
概括

一个新的无损序列压缩器,GraSS,通过使用序列特定的功能来增强DNA和RNA数据的压缩. 这种方法优于现有的算法,为基因组研究提供高效的数据压缩.

关键词:
DNA和RNA序列压缩压缩这是一个很快的速度.语法规则 语法规则 语法规则没有参考的无损压缩.统计规则 统计规则替代规则 替代规则 替代规则

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Novel Sequence Discovery by Subtractive Genomics
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Novel Sequence Discovery by Subtractive Genomics

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相关实验视频

Last Updated: Jun 3, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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科学领域:

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

背景情况:

  • 像Gzip和Zstd这样的通用压缩机由于缺乏序列特定特征利用,对DNA/RNA序列表现不佳.
  • 现有的压缩机需要耗时的参数调整,以实现有效的分子序列压缩.

研究的目的:

  • 推出GraSS,一个新的无参考,无损序列压缩器,专为DNA和RNA数据设计.
  • 为了提高序列压缩效率,利用基于语法,统计和替换规则的方法.

主要方法:

  • 在分子序列数据库中常见的GraSS处理原始,FASTA和多FASTA格式.
  • 压缩机利用DNA和RNA序列的固有特征进行有效的压缩.

主要成果:

  • 格拉斯实现了DNA序列的4.5和RNA序列的19.6的加权平均压缩比 (WACR).
  • DNA序列体的总压缩时间 (TCT) 为246.8秒.
  • 与先进的算法相比,GraSS表现出卓越的性能,特别是对于重复序列,具有竞争力的解压缩时间和资源使用.

结论:

  • 在分子序列的无损压缩方面,GraSS提供了显著的进步.
  • 拟议的方法为处理大规模基因组数据提供了高效和有效的解决方案.