Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

17.0K
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%...
17.0K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.3K
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...
12.3K
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

13.8K
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,...
13.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Identifiability, Sensitivity, and Genetic Algorithms in Bacterial Biofilm Selection Models.

Bulletin of mathematical biology·2026
Same author

Thermal stress disrupts symbiotic fluid dynamics in bobtail squid.

Journal of the Royal Society, Interface·2026
Same author

Enhancing generalizability of model discovery across parameter space with multi-experiment equation learning for biological systems.

PLoS computational biology·2026
Same author

Triple Matrix Factorization for Drug-Drug Interaction Prediction Using Fused Gromov-Wasserstein Distances.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Studying the Effects of Oral Contraceptives on Coagulation Using a Mathematical Modeling Approach.

Mathematical modeling for women's health : Collaborative Workshop for Women in Mathematical Biolog. Collaborative Workshop for Women in Mathematical Biology (2022)·2025
Same author

A stochastic model of prion dynamics with conversion and fragmentation.

Mathematical biosciences·2025

相关实验视频

Updated: May 24, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.0K

在双胞胎物种中进行基因组变异预测的稀有负二项信号恢复.

Jocelyn Ornelas Munoz, Erica M Rutter, Mario Banuelos

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    概括

    这项研究引入了一种新的计算方法,用于检测基因组中的结构变异 (SV). 改进的方法提高了识别遗传变异的准确性,有助于疾病研究.

    科学领域:

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

    背景情况:

    • 结构变异 (SV) 在遗传疾病和多样性中至关重要.
    • 在未知的基因组中检测SV是具有挑战性的,因为稀有性和噪音.
    • 目前的方法依赖于将测序碎片与参考基因组进行比较.

    研究的目的:

    • 开发一种改进的计算方法来检测结构变异 (SV).
    • 提高基因组数据中SV检测的准确性和可靠性.
    • 为应对与罕见变异和低覆盖度测序相关的挑战.

    主要方法:

    • 实现了一个优化方法,使用负二项式日志-概率目标函数.
    • 采用块坐标下降方法,同时预测同卵性/异卵性SVs.
    • 在一个生物现实的子女-父母基因组场景中模拟遗传和新型变异.

    主要成果:

    • 使用模拟数据预测结构变异 (SVs) 的改进.
    • 与现有的方法相比,展示了虚假阳性的增强检测.
    • 在复杂的基因组分析中验证了框架的有效性.

    更多相关视频

    Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
    14:06

    Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

    Published on: June 23, 2012

    15.1K
    Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens
    09:33

    Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

    Published on: August 25, 2023

    1.1K

    相关实验视频

    Last Updated: May 24, 2025

    Rare Event Detection Using Error-corrected DNA and RNA Sequencing
    10:36

    Rare Event Detection Using Error-corrected DNA and RNA Sequencing

    Published on: August 3, 2018

    12.0K
    Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
    14:06

    Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

    Published on: June 23, 2012

    15.1K
    Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens
    09:33

    Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

    Published on: August 25, 2023

    1.1K

    结论:

    • 开发的计算方法在SV检测方面取得了重大进展.
    • 这种方法改善了基因变异的预测,并减少了错误.
    • 该框架为基因组研究和疾病关联研究提供了更强大的工具.