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

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

35
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
35
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

47
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
47

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

Artificial intelligence in animal breeding and genetics: applications, opportunities, and challenges.

Animal frontiers : the review magazine of animal agriculture·2026
Same author

Genetic parameters of behavior traits of beef cattle classified using wearable devices.

Animal science journal = Nihon chikusan Gakkaiho·2024
Same author

An R package for ensemble learning stacking.

Bioinformatics advances·2023
Same author

Assessing the predictability of racing performance of Thoroughbreds using mixed-effects model.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie·2023
Same author

An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference.

Bioinformatics (Oxford, England)·2022
Same author

Genomic prediction with non-additive effects in beef cattle: stability of variance component and genetic effect estimates against population size.

BMC genomics·2021

相关实验视频

Updated: Jun 17, 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

669

用代谢网络进行基因组预测的贝叶斯模型.

Akio Onogi1

  • 1Department of Life Sciences, Faculty of Agriculture, Ryukoku University, Otsu, Shiga 520-2194, Japan.

Bioinformatics advances
|August 12, 2024
PubMed
概括

这项研究引入了一种新的贝叶斯模型,以提高使用omics数据的基因组预测准确度. 综合模型通过分析代谢网络反应来增强生物质预测,优于以前的多步骤方法.

科学领域:

  • 基因组学就是基因组学.
  • 系统生物学 系统生物学
  • 代谢工程是代谢工程.

背景情况:

  • 基因组预测在育种和医学方面至关重要.
  • Omics数据集成可以提高预测的准确性.
  • 以前用于生物质预测的代谢网络方法存在局限性.

研究的目的:

  • 为改进基因组预测开发一个集成的贝叶斯模型.
  • 利用代谢网络信息来提高生物质预测的准确性.
  • 为了克服多步预测方法的局限性.

主要方法:

  • 开发了一个贝叶斯模型,将多个步骤集成到一个框架中.
  • 与生物质生产相关的联合推断的反应流.
  • 使用模拟和真实生物数据验证了模型.

主要成果:

  • 与现有方法相比,提出的贝叶斯模型显示出更高的预测准确度.
  • 代谢网络信息的整合在生物质预测方面被证明是有效的.
  • 该模型成功预测了Arabidopsis中的生物质生产.

结论:

更多相关视频

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

3.2K
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

2.3K

相关实验视频

Last Updated: Jun 17, 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

669
A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

3.2K
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

2.3K
  • 综合贝叶斯方法为基因组预测提供了更准确的方法.
  • 代谢网络数据是改善预测模型的宝贵资源.
  • 开发的模型为育种和医学领域的应用提供了强大的工具.