Search research articles

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 Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

相关概念视频

What is Population Genetics?

What is Population Genetics?

A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.

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

Protocol for genotyping cephalopod sex using a skin swab and quantitative PCR.

STAR protocols·2026

Same author

MKado: a toolkit for McDonald-Kreitman tests of natural selection.

G3 (Bethesda, Md.)·2026

Same author

Ecotypes, <i>Wolbachia</i>, and urbanization shape <i>Culex pipiens</i> population structure in a West Nile virus hotspot.

bioRxiv : the preprint server for biology·2026

Same author

Diversity and divergence of two sympatric, sibling octopus species.

bioRxiv : the preprint server for biology·2026

Same author

A non-invasive method to genotype cephalopod sex by quantitative PCR.

iScience·2026

Same author

Neural posterior estimation for population genetics.

Genetics·2026

Search research articles

相关实验视频

Updated: Jun 16, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

通过神经网络使用多态数据对空间人口图的估计.

Chris C R Smith¹, Gilia Patterson¹, Peter L Ralph¹

¹Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA.

Molecular ecology resources

|August 17, 2024

概括

此摘要是机器生成的。

本研究引入了一种新的深度神经网络方法,使用地理参考单核酸多态 (SNP) 数据绘制人口密度和分散率的地图. 该工具提供了一种独特的方法来了解景观遗传学,并为保护工作提供信息.

关键词:

保护遗传学保护遗传学生态遗传学生态遗传学机器学习是机器学习.人口遗传学人口遗传学野生动物管理野生动物管理

更多相关视频

Topographical Estimation of Visual Population Receptive Fields by fMRI

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

相关实验视频

Last Updated: Jun 16, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Topographical Estimation of Visual Population Receptive Fields by fMRI

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

科学领域:

人口遗传学人口遗传学
风景遗传学风景遗传学
计算生物学计算生物学

背景情况:

了解遗传变异如何在整个景观中分布,对于人口遗传学至关重要.
众所周知,异质的人口密度和分散障碍会影响遗传变异.
现有的工具往往难以解释这些复杂的空间因素.

研究的目的:

开发一种新的推断方法,用于估计人口密度和分散率的空间异质地图.
使用地理参考单核酸多态 (SNP) 数据与深度神经网络用于人口参数估计.
提供一种工具,可以推断分散和密度的幅度和空间变化.

主要方法:

使用模拟的基因型和采样位置数据训练了一个深度神经网络.
该网络从SNP数据中学会了预测人口参数 (密度和分散率).
该方法与现有的人口遗传学推断工具进行了比较.

主要成果:

开发的方法成功地从模拟数据中估计了空间异质的人口参数.
对北美灰狼数据的应用产生了合理的人口统计估计,尽管受到采样的影响.
该工具使用SNP数据独特地推断出分散大小和密度变化,与仅限于相对迁移率的方法不同.

结论:

新的深度神经网络方法为推断景观层面的人口流程提供了有价值的工具.
该方法补充了现有的直接人口统计估计技术.
该开源软件促进了保护,生态和进化生物学领域的应用.