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

Epistasis Analysis01:09

Epistasis Analysis

4.9K
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...
4.9K
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

329
Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
329
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

102
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
102
Pleiotropy01:33

Pleiotropy

39.9K
Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
39.9K
Modeling and Similitude01:12

Modeling and Similitude

245
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
245
Multiple Allele Traits01:49

Multiple Allele Traits

34.0K
The Concept of Multiple Allelism
34.0K

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

Autonomous biomedical research with an artificial intelligence agent.

Science (New York, N.Y.)·2026
Same author

ProMeta: a meta-learning framework for robust disease diagnosis and prediction from plasma proteomics.

Bioinformatics (Oxford, England)·2026
Same author

LOESS and DE-SWAN can induce artifactual "waves" of molecular aging.

bioRxiv : the preprint server for biology·2026
Same author

The gut microbiome of a Northern Plains tribe is in transition between global Indigenous and industrialized populations.

Cell reports·2026
Same author

Reply to I Jannasz et al: DIETFITS cohort, modeling, and molecules.

The American journal of clinical nutrition·2026
Same author

Towards the construction of a virtual yeast.

Nature·2026

相关实验视频

Updated: Jun 7, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

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

Published on: March 1, 2024

643

在多基因预测中通过几何深度学习建模基因相互作用.

Han Li1,2, Jianyang Zeng3, Michael P Snyder4

  • 1School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, China.

Genome research
|November 19, 2024
PubMed
概括

这项研究介绍了PRS-Net,这是一种用于预测复杂疾病遗传风险的新型深度学习框架. PRS-Net有效地模拟基因相互作用,优于精准医学和生物发现的传统方法.

更多相关视频

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.1K
In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

20.6K

相关实验视频

Last Updated: Jun 7, 2025

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

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

Published on: March 1, 2024

643
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.1K
In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

20.6K

科学领域:

  • 遗传学 遗传学 是一个
  • 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:

  • 多基因风险评分 (PRS) 对精准医学至关重要,但传统的线性模型在复杂的基因型-表型关系中扎.
  • 现有的PRS方法往往无法捕捉复杂疾病背后的复杂,非线性生物相互作用.

研究的目的:

  • 开发一个可解释的几何深度学习框架,PRS-Net,用于增强遗传风险预测和生物发现.
  • 模拟生物系统的非线性和基因对基因相互作用,以改善疾病预测.

主要方法:

  • PRS-Net使用图形神经网络 (GNN) 在解构全基因组PRS后建模基因-基因相互作用.
  • 一个专注的读取模块被纳入,以提高模型的可解释性.
  • 该框架在多种复杂的特征和疾病中进行了测试.

主要成果:

  • 与传统的PRS方法相比,PRS-Net表现出优异的预测性能.
  • 该模型成功识别了与疾病相关的基因和生物通路.
  • 在预测复杂疾病的遗传风险方面取得了更高的准确性.

结论:

  • PRS-Net为复杂疾病中的遗传风险预测和生物发现提供了一个强大的,可解释的工具.
  • 该框架通过有效地建模复杂的生物系统来推进精密医学.
  • 突出了几何深度学习在理解疾病病因学方面的潜力.