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相关概念视频

Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...
Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in value between...
Factors Influencing Attraction III: Similarity01:23

Factors Influencing Attraction III: Similarity

The similarity hypothesis suggests that individuals are more likely to form relationships with others who share similar attitudes, beliefs, values, and interests. This concept has been widely studied in social psychology, demonstrating that perceived similarity fosters interpersonal attraction. In an experiment supporting this hypothesis, participants were presented with fabricated information indicating that strangers held attitudes similar to their own. The results showed that participants...
Causes of Similarity-Dissimilarity Effect01:26

Causes of Similarity-Dissimilarity Effect

The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...

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相关实验视频

Updated: Jun 14, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

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SigAlign:一个由明确的相似性标准指导的对齐算法.

Kunhyung Bahk1, Joohon Sung1,2

  • 1Interdisciplinary Program in Bioinformatics, College of Natural Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea.

Nucleic acids research
|July 16, 2024
PubMed
概括

SigAlign提供了一种新的,非启发式的生物序列对齐方法. 它实现了高吞吐量和灵敏度,超过了针对特定数据类型的现有工具.

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:

  • 生物序列对齐中的启发性对齐器通过近似技术提供高吞吐量.
  • 这些方法经常牺牲输出清晰度,并引入复杂的参数空间.
  • 需要具有透明标准和可定制参数的调整算法.

研究的目的:

  • 介绍SigAlign,一个新的对齐算法,解决启发式方法的局限性.
  • 为生物信息学工具和管道提供透明和可定制的调整过程.
  • 通过明确的切断和亲属差距处罚来增强生物序列对齐.

主要方法:

  • 开发了SigAlign,一个非启发式对齐算法.
  • 实施的明确切线:每条长度的最小长度和最大惩罚.
  • 整合了三个相似差距处罚.
  • 与领先的工具进行了比较分析:BLASTn,MMseqs2,BWA-MEM,bowtie2,HISAT2和minimap2.

主要成果:

  • 在比较分析中,SigAlign表现出高度的灵敏度和吞吐量.
  • 优于现有的启发式对齐器,特别是在高精度读取或低重复性内容的基因组.

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  • 在读取映射和数据库搜索任务中实现卓越的性能.
  • SigAlign提供了一个非启发式的方法,具有明确,可理解的输出标准.
  • 结论:

    • SigAlign为启发式对齐方法提供了一个可行的替代方案.
    • 它的透明性和可定制性使得它适合整合到各种生物信息管道中.
    • 该算法提高了生物序列对齐效率和清晰度.
    • SigAlign被发布为一个开源库,以促进进一步的开发和采用.