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相关概念视频

Adjusting a Traverse01:12

Adjusting a Traverse

59
In the site survey of a four-sided traverse, internal angles are essential to ensure geometric accuracy. The survey revealed that the sum of the measured internal angles was 359 degrees and 48 minutes, which is 12 minutes less than the expected 360 degrees. This discrepancy signals an error likely arising from measurement inaccuracies during the fieldwork.To rectify this error, the adjustment process involved distributing the 12-minute shortfall equally across the four internal angles. By...
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Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
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RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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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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相关实验视频

Updated: Jul 5, 2025

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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准确的全球对齐使用A*与链接种子启发式和匹配修剪.

Ragnar Groot Koerkamp1, Pesho Ivanov1

  • 1Department of Computer Science, ETH Zurich, Rämistrasse 101, Zurich 8092, Switzerland.

Bioinformatics (Oxford, England)
|January 24, 2024
PubMed
概括

一个新的A*PA对齐器使用A*最短路径算法提供更快的精确对齐. 它实现了显著的加快速度,特别是在具有高分歧的长DNA序列中,改善了计算生物学研究.

科学领域:

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

背景情况:

  • 序列对齐是计算生物学的基础.
  • 现有的精确对齐算法与长序列和高分歧作斗争.

研究的目的:

  • 开发一种实用的算法,以在线性时间内准确地对齐顺序.
  • 为了提高对长和分离的序列对齐的效率.

主要方法:

  • 使用A*最短路径算法来实现完全的全球对齐.
  • 扩展种子启发式与匹配链,差距成本,和不准确的匹配.
  • 集成匹配修剪和对角过渡用于增强的A*搜索.

主要成果:

  • A*PA 显示了近线性运行时间缩放 (n^1.06 到 n^1.24) 对于最多 107 bp 的序列.
  • 在4%的分歧下,在107bp的序列中实现了超过Edlib和BiWFA的500倍的加速度.
  • 在长时间的ONT读取 (人体样本) 上显示了3倍的中位速度,差异<10%.
  • 对于来自不同人体样本的序列,执行速度比Edlib和BiWFA快1.7倍.

结论:

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  • A*PA对齐器在精确的对齐效率方面取得了显著的进步.
  • 该算法的性能在各种序列长度和分歧水平上是稳定的.
  • A*PA是分析大型基因组数据集的宝贵工具,特别是长读数和分歧序列.