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関連する概念動画

Sanger Sequencing01:57

Sanger Sequencing

775.6K
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...
775.6K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

8.3K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
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Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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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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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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Updated: Feb 21, 2026

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
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ゲノム全体の整列を加速するminimap2

Ghanshyam Chandra1, Md Vasimuddin2, Sanchit Misra2

  • 1Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, 560012, KA, India.

Bioinformatics (Oxford, England)
|February 19, 2026
PubMed
まとめ
この要約は機械生成です。

新しい全ゲノムアライナメントソフトウェア,mm2-plusは,長読シーケンシングデータの効率性を向上させます. CPUの使用を最適化することでアライメントを加速し,精度を犠牲にすることなくより速い結果をもたらします.

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Last Updated: Feb 21, 2026

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
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G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

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A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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科学分野:

  • ゲノミクスゲノミクスとは
  • バイオインフォマティックス

背景:

  • ロングリードシーケンシングは,クロモソームを網羅する大規模なDNAシーケンスを生成します.
  • 現在の全ゲノムアライナメントツールは,より少ない,より長いシーケンスにより並列化の効率が低下し,CPUが不足し,実行時間が増加します.

研究 の 目的:

  • 長い読み込みのシーケンシングデータのためのより速く,より効率的な全ゲノムアライナメント方法を開発する.
  • 既存のアライナメントツールのサブ最適のCPU利用とより長いランタイムに対処するために.

主な方法:

  • ミニマップ2アライナーを改良したバージョンであるmm2-plusを開発した.
  • 細粒子の並列連鎖アルゴリズムを実装しました.
  • プライマリとセカンダリアライナメントチェーンを区別するための迅速な方法を導入した.

主要な成果:

  • 人間,植物,霊長類のゲノム全体の整列を大幅に加速した.
  • 観測されたスピードアップは1.6×から7.2×まででした.
  • 配列の精度は,既存の方法と同等に保たれています.

結論:

  • mm2-plusは,長時間読まれた配列データの全ゲノム整合の速度と効率を大幅に改善します.
  • 最適化は,大規模で連続したゲノム配列によって引き起こされる課題を効果的に解決します.
  • この進歩は,ゲノム解析パイプラインの加速に不可欠です.