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相关概念视频

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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.
GWAS does not require the identification of the target gene involved in...
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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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Protein-protein Interfaces02:04

Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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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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Epistasis Analysis01:09

Epistasis Analysis

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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...
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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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相关实验视频

Updated: Jun 18, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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生物医学文献挖掘:基于图核的学习,用于基因基因相互作用的提取.

Ai-Ru Hsieh1, Chen-Yu Tsai2

  • 1Department of Statistics, Tamkang University, Tamsui District, New Taipei City, 251301, Taiwan. airudropbox@gmail.com.

European journal of medical research
|August 2, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的远程监控方法,可以自动提取基因相互作用,从而降低手动注释成本. 这种方法有助于理解复杂疾病的遗传性,并推进精准医学.

关键词:
生物医学文本挖掘技术基因基因相互作用图形内核的图形内核是什么

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Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
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科学领域:

  • 生物医学信息学是生物医学信息学.
  • 机器学习 机器学习
  • 基因组学就是基因组学.

背景情况:

  • 监督机器学习用于生物医学关系提取需要大量的手动注释.
  • 现有的方法缺乏对基因-基因相互作用的关注,这对于理解复杂疾病至关重要.
  • 远程监控通过利用自动注释的知识库提供了一个切实可行的替代方案.

研究的目的:

  • 开发和评估一种用于提取基因相互作用的自动化方法.
  • 解决生物医学关系提取研究中的差距,专注于基因-基因相互作用.
  • 促进对人类复杂疾病遗传性的理解.

主要方法:

  • 使用KEGG PATHWAY数据库获取基因相互作用信息.
  • 从PubMed摘要生成了一个培训数据集.
  • 使用图形内核方法来提取关系.
  • 实施了远程监督方法,以消除手动标签.

主要成果:

  • 在基因对基因相互作用提取方面获得了0.79的高F1得分.
  • 成功证明了远程监控方法的有效性.
  • 在这个领域验证了图形内核方法的适用性.

结论:

  • 开发的远程监控方法显著减少了与手动数据注释相关的时间和成本.
  • 基于图核的方法对于提取基因相互作用是有效的.
  • 预计这项工作将有助于精准医学的进步.