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

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

101
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
101
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

68
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...
68
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

8.5K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
8.5K
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.1K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.1K
The Integrated Rate Law: The Dependence of Concentration on Time02:39

The Integrated Rate Law: The Dependence of Concentration on Time

35.5K
While the differential rate law relates the rate and concentrations of reactants, a second form of rate law called the integrated rate law relates concentrations of reactants and time. Integrated rate laws can be used to determine the amount of reactant or product present after a period of time or to estimate the time required for a reaction to proceed to a certain extent. For example, an integrated rate law helps determine the length of time a radioactive material must be stored for its...
35.5K
Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

202
According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
202

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

Prescribing and dispensing patterns of asthma medications among children on the Navajo Nation.

The journal of allergy and clinical immunology. In practice·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

Sparse Negative Binomial Signal Recovery for Genomic Variant Prediction in Diploid Species.

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

Parameter estimation and identifiability analysis for a bivalent analyte model of monoclonal antibody-antigen binding.

Analytical biochemistry·2023

相关实验视频

Updated: Jul 28, 2025

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
10:07

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

6.2K

使用聚合时空数据对反应-扩散方程与竞争的参数分布的估计.

Kyle Nguyen1,2, Erica M Rutter3, Kevin B Flores4,5

  • 1Biomathematics Graduate Program, North Carolina State University, Raleigh, NC, USA.

Bulletin of mathematical biology
|June 2, 2023
PubMed
概括

这项研究引入了一种新的随机微分方程模型,以准确预测竞争性亚种群中的细胞密度,优于传统模型. 这种方法增强了对生物种群动态和癌症生长的理解.

关键词:
质母细胞瘤多形参数估计的参数估计.随机微分方程 随机微分方程k-意味着集群的集群.

更多相关视频

Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells
10:21

Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells

Published on: September 16, 2020

6.2K
Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
10:20

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

8.3K

相关实验视频

Last Updated: Jul 28, 2025

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
10:07

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

6.2K
Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells
10:21

Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells

Published on: September 16, 2020

6.2K
Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
10:20

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

8.3K

科学领域:

  • 数学生物学 数学生物学
  • 计算生物学 计算生物学
  • 癌症建模 癌症建模

背景情况:

  • 反应-扩散方程模拟人口动态,但通常假定均的速率.
  • 现实世界的人口经常由具有不同特征的相互竞争的子人口组成.
  • 现有的推断表型异质性的方法在竞争的子群体方面存在局限性.

研究的目的:

  • 将现有的推断表型异质性的方法扩展到具有竞争性亚种群的反应扩散模型.
  • 开发和测试一种新的随机微分方程模型,用于分析复杂的人口动态.
  • 将开发的模型应用于多形质母细胞瘤 (GBM) 癌症的生长.

主要方法:

  • 通过转换反应扩散模型,开发了一种新的随机微分方程模型.
  • 使用Prokhorov度量框架进行参数分布估计.
  • 应用k-means集群,以根据估计的分布预测子群的数量.
  • 模拟数据模拟实际测量,用于模型验证.

主要成果:

  • 与传统的部分微分方程模型相比,新的随机微分方程模型在预测细胞密度方面表现出更高的准确性.
  • 该模型被证明比现有方法更节省时间.
  • 成功估计了异构亚群中扩散和增长率的联合分布.
  • K-means集群有效地预测了子群的数量.

结论:

  • 开发的随机微分方程方法有效地模拟了竞争分群中的表型异质性.
  • 这种方法为分析复杂的生物系统,包括癌症扩散提供了更准确,更有效的工具.
  • 这些发现为了解和潜在地控制各种生物环境中的种群动态提供了强大的框架.