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相关概念视频

Variation01:19

Variation

7.7K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
7.7K
Epistasis01:39

Epistasis

50.1K
In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
50.1K
Variability: Analysis01:11

Variability: Analysis

444
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
444
Leaky Scanning02:28

Leaky Scanning

5.6K
During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
5.6K
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

471
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
471
Epistasis Analysis01:09

Epistasis Analysis

5.7K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
5.7K

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相关实验视频

Updated: Jan 15, 2026

Functional Characterization of Endogenously Expressed Human RYR1 Variants
07:59

Functional Characterization of Endogenously Expressed Human RYR1 Variants

Published on: June 9, 2021

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结构和变异效应预测器在RyR1临床解释中的互补作用

Rolando Hernández Trapero1, Mihaly Badonyi1, Lukas Gerasimavicius1

  • 1MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.

Human mutation
|October 13, 2025
PubMed
概括

这项研究引入了一种新的方法,即空间接近疾病变异 (SPDV),以更好地解释RYR1相关疾病中的遗传变异. SPDV使用蛋白质结构来改善当前工具不足时的诊断.

科学领域:

  • 遗传学和分子生物学
  • 生物化学 生物化学
  • 计算生物学 计算生物学

背景情况:

  • 与RyR1相关的疾病源于RYR1基因变异,呈现不同的表型.
  • 由于基因长度和变异机制,解释RYR1变异具有挑战性.
  • 当前变异效应预测器 (VEP) 的性能有限,具有固有的偏见.

研究的目的:

  • 为了评估70个VEPs对RYR1误解变体分类的有效性.
  • 引入一种基于蛋白质结构的新型指标,即疾病变异的空间接近度 (SPDV).
  • 帮助临床解释不确定意义的RYR1变异.

主要方法:

  • 使用致病性和良性RYR1误解变体评估了70个VEP.
  • 引入了SPDV,这是一种基于3D病原突变聚类的指标.
  • 确定了SPDV和顶级VEP的ACMG/AMP PP3/BP4分类值.

主要成果:

  • 现有的VEP显示了可变的性能;那些在临床数据上接受培训的人由于循环性而提高了性能.
  • 减少训练偏差的VEP显示出有限的表现,可能缺少功能增益变体.
  • SPDV在将PP3/BP4证据水平分配给不确定的RYR1变体方面证明了实用性.
关键词:
功能收益的功能收益.错误的意义变体的变体氨酸受体是氨酸的受体.结构生物信息学变异效应预测器的变异效应预测器变体解释变体解释

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Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

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Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis
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Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis

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相关实验视频

Last Updated: Jan 15, 2026

Functional Characterization of Endogenously Expressed Human RYR1 Variants
07:59

Functional Characterization of Endogenously Expressed Human RYR1 Variants

Published on: June 9, 2021

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Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
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Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Published on: June 6, 2025

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Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis
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Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis

Published on: June 17, 2019

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结论:

  • 一种基于蛋白质结构的新方法 (SPDV) 为现有的VEP提供了一个直角的策略.
  • SPDV有助于RyR1相关疾病的诊断过程.
  • 这种方法有助于克服当前用于变量解释的计算工具的局限性.