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 Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

34
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...
34
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.2K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.2K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

257
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
257
Survival Tree01:19

Survival Tree

44
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
44
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

3.9K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
3.9K
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

27
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
27

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

ProphDR: An Interpretable Deep Learning Model for Predicting Cancer Drug Response via Multi-Omics and Cross-Attention Mechanisms.

Journal of chemical information and modeling·2026
Same author

AI decodes protein-ligand binding.

Nature chemical biology·2026
Same author

Generative AI for controllable protein sequence design: A survey.

npj drug discovery·2026
Same author

Unified heterogeneity-aware benchmark of drug synergy prediction: a cross-study analysis of traditional machine learning and graph deep learning models.

Journal of cheminformatics·2026
Same author

Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.

Nature protocols·2026
Same author

EpiMII: Structure-Aware Graph Neural Networks for MHC-II Epitope Generation.

Research (Washington, D.C.)·2026

相关实验视频

Updated: May 16, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

12.9K

一种基于帕雷托算法和蒙特卡洛树搜索的多目标分子生成方法.

Yifei Liu1, Yiheng Zhu2, Jike Wang1

  • 1College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, P. R. China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|April 4, 2025
PubMed
概括

新的帕雷托蒙特卡洛树搜索分子生成 (PMMG) 方法有效地优化了多种药物发现目标. 这种先进的算法可显著加速识别具有所需特性的新药候选药物.

关键词:
药物设计 药物设计分子生成分子的产生.多目标优化多目标优化帕雷托最佳性是最优的

更多相关视频

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.6K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.5K

相关实验视频

Last Updated: May 16, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

12.9K
Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.6K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.5K

科学领域:

  • 计算化学是一种计算化学.
  • 药物发现 药物发现
  • 医学中的人工智能

背景情况:

  • 药物发现受到同时优化多个分子目标的挑战的阻碍.
  • 目前的计算方法在处理四个以上的目标上是有限的,限制了分子设计的进步.

研究的目的:

  • 引入一种新的方法,帕雷托蒙特卡洛树搜索分子生成 (PMMG),用于多目标分子设计.
  • 克服高维客观空间中现有算法的局限性.

主要方法:

  • 利用蒙特卡罗树搜索 (MCTS) 有效地探索化学空间并识别帕雷托前线.
  • 采用简化分子输入线输入系统 (SMILES) 来进行分子表示.
  • 应用PMMG以优化多种药物发现目标,包括结合亲缘关系和药物相似性.

主要成果:

  • 在同时优化七个目标方面,PMMG取得了51.65%的成功率,超过现有方法的2.5倍.
  • 证明了PMMG在产生对EGFR和HER2点具有高对接分数的分子的能力.
  • 生成的分子具有有利的预测类似药物的特性.

结论:

  • PMMG有效地解决了分子设计中多目标优化的挑战.
  • 该方法显示了通过处理众多复杂的目标来加速药物发现管道的巨大潜力.
  • PMMG代表了用于识别新药候选者的计算方法的实质性进步.