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相关概念视频

Genomics02:02

Genomics

36.3K
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...
36.3K
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

18.9K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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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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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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Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
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用深度学习技术对整个和复杂的基因组区域进行基因型赋值方法,利用深度学习技术.

Tatsuhiko Naito1,2, Yukinori Okada3,4,5,6,7

  • 1Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita-shi, Osaka, 565-0871, Japan. tnaito@sg.med.osaka-u.ac.jp.

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|January 15, 2024
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概括

深度学习改善了人类遗传研究的基因型归因,提供了隐私利益和效率. 虽然准确度的增长很小,但未来的进步有望在全基因组关联研究中提高预测和可用性.

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科学领域:

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

背景情况:

  • 基因型归算对于人类遗传研究至关重要,它增强了全基因组关联研究 (GWAS) 和精细映射.
  • 已经出现了用于基因型归因的深度学习方法,能够建模复杂的链接不平衡模式.
  • 这些方法也应用于特定区域,如人类白细胞抗原 (HLA) 归算的主要基因相容性综合体 (MHC).

研究的目的:

  • 审查基于深度学习的基因型归算方法的现状和潜力.
  • 突出这些先进的计算技术的优势和局限性.
  • 讨论遗传数据分析中的深度学习的未来轨迹.

主要方法:

  • 对最近基于深度学习的基因型归算算法进行审查.
  • 与传统的统计和机器学习方法相比,分析它们的性能.
  • 评估它们在全基因组和特定区域 (如HLA) 的应用.

主要成果:

  • 深度学习方法提供了一个"无引用"的方法,确保数据隐私和高计算效率.
  • 目前的深度学习归算方法显示了与现有技术相比适度的准确性改进.
  • 这些方法表明了复杂的链接不平衡模式学习的潜力.

结论:

  • 基于深度学习的基因型归因在遗传研究中呈现出一个有希望的,保护隐私的,高效的替代方案.
  • 预计深度学习的进一步进展将大大提高预测准确性和实际可用性.
  • 这些方法有望成为越来越有价值的工具,用于遗传数据分析和发现.