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相关概念视频

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

15.2K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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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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Genetic Screens02:46

Genetic Screens

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
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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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Updated: Jul 12, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

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TSPLASSO:一个两阶段的先前LASSO算法,用于使用Omics数据进行基因选择.

Sijia Yang, Shunjie Chen, Pei Wang

    IEEE journal of biomedical and health informatics
    |October 23, 2023
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    此摘要是机器生成的。

    这项研究引入了TSPLASSO,一种新的两阶段特征选择方法,通过结合先前知识,有效地从omics数据中识别癌症基因. TSPLASSO显著提高了基因选择精度和样本分类,以改善癌症研究.

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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:

    • 特性选择对于从omics数据中识别癌症基因至关重要.
    • 现有的方法往往忽略了关于已知的癌症基因的宝贵先验知识.
    • 整合先前的癌症基因信息可以提高特征选择的准确性.

    研究的目的:

    • 为癌症基因鉴定提出一种新的前期 LASSO (TSPLASSO) 两阶段方法.
    • 在特征选择过程中利用已知癌症基因的先前知识.
    • 使用omics数据同时进行癌症基因选择和样本分类.

    主要方法:

    • TSPLASSO采用使用 LASSO 回归的双阶段方法.
    • 第一阶段使用线性回归来选择与先前的癌症基因相关的候选基因.
    • 第二阶段使用后勤回归来进行最终的基因选择和样本分类.

    主要成果:

    • 在多个数据集中,TSPLASSO在变量选择准确度方面表现出显著的改进 (5% - 400%).
    • 该方法在数据噪声和先前癌症基因信息变异方面表现出强度.
    • 在精度和稳定性方面,TSPLASSO超过了六个最先进的算法.

    结论:

    • TSPLASSO提供了一种高效,稳定和实用的算法,用于从omics数据中发现癌症基因.
    • 该方法有效地将先前的生物学知识与特征选择相结合.
    • 通过改进omics数据的分析,TSPLASSO促进了生物医学和健康信息学的发展.