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相关概念视频

Evolutionary Relationships through Genome Comparisons02:54

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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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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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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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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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使用加密的基因型和表型进行合作基因组分析,以保持数据保密性.

Tianjing Zhao1,2, Fangyi Wang3, Richard Mott4

  • 1Department of Animal Science, University of California, Davis, CA 95616, USA.

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概括

对基因型和表型 (HEGP) 的同型加密使得安全的农业基因组研究成为可能. 这种方法允许共享基因组对基因组分析的数据,同时保护隐私和知识产权.

关键词:
在GWAS中,GWAS就是GWAS.基因组预测 基因组预测同型型的加密方式.联合分析 联合分析这是一个混合模型混合模型.

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科学领域:

  • 农业基因组学 农业基因组学
  • 生物信息学是一种生物信息学.
  • 数据安全数据安全

背景情况:

  • 公平原则促进农业基因组对现象研究中的数据共享.
  • 隐私和知识产权问题阻碍了数据共享.
  • 现有的方法缺乏安全的基因组数据分析的强大解决方案.

研究的目的:

  • 扩展对基因型和表型 (HEGP) 的同型加密,用于更广泛的基因组到现象应用.
  • 为了实现安全的合作基因组分析,同时保持数据保密性.
  • 促进在农业研究中采用FAIR原则.

主要方法:

  • 扩展对基因型和表型 (HEGP) 的同型加密方法.
  • 将HEGP应用于线性混合模型,包括基因组最佳线性无偏预测 (GBLUP) 和回归最佳线性无偏预测 (RR-BLUP).
  • 整合HEGP与贝叶斯变量选择方法进行基因分析.

主要成果:

  • HEGP适用于各种遗传分析,包括参数估计,基因组预测和全基因组关联研究 (GWAS).
  • 扩展的HEGP方法在统计分析期间保持数据保密.
  • 已证明适用于常用于定量特征遗传学的复杂遗传模型.

结论:

  • 先进的HEGP方法为合作的农业基因组研究提供了安全有效的方法.
  • 在基因组对现象研究中,HEGP有效地解决了隐私和知识产权障碍.
  • 这有利于更大的数据共享和可重复使用性,与FAIR原则保持一致.