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

pV-Diagrams01:18

pV-Diagrams

The pV diagram, which is a graph of pressure versus volume of the gas under study, is helpful in describing certain aspects of the substance. When the substance behaves like an ideal gas, the ideal gas equation describes the relationship between its pressure and volume. On a pV diagram, it is common to plot an isotherm, which is a curve showing p as a function of V with the number of molecules and the temperature fixed. Then, for an ideal gas, the product of the pressure of the gas and its...
Statgraphics01:10

Statgraphics

Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
Interpreting X̄ Charts01:13

Interpreting X̄ Charts

Interpreting x̄ charts, a type of control chart used in statistical process control helps monitor the variation in processes over time. The x̄ chart is based on the sample mean and allows for monitoring variations in the process mean over time. These charts are pivotal for quality assurance in manufacturing and other sectors.
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line represents the process mean,...

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

Bayesian Modeling of Polarizable Water: Lessons for Force Field Development.

Journal of chemical theory and computation·2026
Same author

LacI strikes a balance between stability and inducibility.

Nucleic acids research·2026
Same author

Beyond Partitioning: Using Force Field Science to Evaluate Electrostatics Models.

Journal of chemical theory and computation·2026
Same author

Correction to "Impact of Combination Rules, Level of Theory, and Potential Function on the Modeling of Gas- and Condensed-Phase Properties of Noble Gases".

Journal of chemical theory and computation·2025
Same author

Point + Gaussian charge model for electrostatic interactions derived by machine learning.

Physical chemistry chemical physics : PCCP·2025
Same author

The need to implement FAIR principles in biomolecular simulations.

Nature methods·2025
Same journal

Advancing Biochemical Molecule Registration, Representation and Search for New Drug Modalities.

Journal of chemical information and modeling·2026
Same journal

A Unified Molecular Graph and Protein Language Model Framework for Predicting Human Drug-Hormone Receptor Interactions with Structure-Aware Validation.

Journal of chemical information and modeling·2026
Same journal

Intricate Role of Cholesterol in Membrane Fusion.

Journal of chemical information and modeling·2026
Same journal

tmGNN-XAI: An Explainable Graph Neural Network Tool for Predicting Electronic Properties of Transition Metal Complexes from SMILES.

Journal of chemical information and modeling·2026
Same journal

QSAR in the Browser: An Interactive Cheminformatics Web Application.

Journal of chemical information and modeling·2026
Same journal

FoldDoF: Utilizing the Primary Degrees of Freedom of Protein Backbone for Geometric Modeling and Generation.

Journal of chemical information and modeling·2026
查看所有相关文章

相关实验视频

Updated: Jun 15, 2026

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

3.3K

plotXVG:从GROMACS输出中批量生成出版物质量图表

Måns K Rosenbaum1, David van der Spoel1

  • 1Department of Cell and Molecular Biology, Uppsala University, Uppsala SE-75124, Sweden.

Journal of chemical information and modeling
|March 10, 2026
PubMed
概括
此摘要是机器生成的。

研究人员开发了plotXVG,这是一个免费的Python工具,用于从分子模拟数据中创建出版品质的数据. 这个工具简化了为手稿和机器学习应用程序生成线图,热图和轮图的生成.

更多相关视频

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

2.0K
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

1.4K

相关实验视频

Last Updated: Jun 15, 2026

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

3.3K
Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

2.0K
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

1.4K

科学领域:

  • 计算化学是一种计算化学.
  • 数据可视化数据可视化
  • 科学软件开发科学软件开发

背景情况:

  • 像GROMACS这样的分子模拟软件可以生成大量的时间序列数据.
  • 从这些数据中创建出版品质的数据通常需要商业软件或定制脚本.
  • 越来越多的数据需要有效和可重复的可视化方法.

研究的目的:

  • 介绍plotXVG,这是一个用户友好的Python工具,用于生成出版品质的图形.
  • 为从分子模拟和其他来源提供快速和可重复的数据可视化提供解决方案.
  • 为非程序员和将可视化集成到机器学习工作流程中的人提供灵活性.

主要方法:

  • 在Python中使用了Matplotlib绘图库.
  • 开发了一个简单的工具,plotXVG,具有可访问的界面.
  • 启用了线图,热图和轮图的生成.
  • 为高级集成提供了一个可选的应用程序编程接口 (API).

主要成果:

  • plotXVG可以为各种情节类型生成出版品质的图形.
  • 该工具有助于快速和可重复创建图形文件.
  • 它支持来自分子模拟和其他科学领域的数据.
  • 该软件是免费和开源的,允许用户自定义.

结论:

  • plotXVG提供了一种高效,可复制和可访问的科学数据可视化方法.
  • 该工具使高质量的图形的创作变得民主化,支持手稿编制和计算研究.
  • 它的开源性质鼓励社区贡献和适应.