EMMA - Markov Model Algorithms

This project is no longer supported. Please switch to pyEMMA: <a href="http://pyemma.org">http://pyemma.org</a>Markov models, often called Markov state models (MSMs) or kinetic transition networks, are concise and easy-to-analyze discrete models of continuous stochastic processes. They have been extensively used in the analysis of molecular dynamics (MD). The EMMA software provides a number of command line tools that provide the basics of construction, validation and analysis of Markov models. EMMA is Java-based. <br/><br/>This project includes the following software/data packages: <br/> <ul> <li> <a href="https://simtk.org/frs?group_id=513#pack_854">EMMA </a> : Command line tools and documentation of EMMA </li> <li> <a href="https://simtk.org/frs?group_id=513#pack_1218">GSGS-peptide data </a> : Siulation data from a Gromacs simulation of MR121-GSGS-W - peptide. For more information refer to the documentation </li> <li> <a href="https://simtk.org/frs?group_id=513#pack_1416">Tica Data </a> : Two distance trajectories needed as input for the tica module of EMMA </li> </ul>

本项目现已停止维护。请转而使用pyEMMA：[访问pyEMMA](http://pyemma.org)。马尔可夫模型，通常被称为马尔可夫状态模型（MSM）或动力转换网络，是连续随机过程的简洁且易于分析的离散模型。它们在分子动力学（MD）分析中得到了广泛的应用。EMMA软件提供了一系列命令行工具，用于马尔可夫模型的构建、验证和分析。EMMA软件基于Java语言开发。

本项目包含以下软件/数据包：

<ul>
<li><a href="https://simtk.org/frs?group_id=513#pack_854">EMMA</a>：EMMA的命令行工具和文档</li>
<li><a href="https://simtk.org/frs?group_id=513#pack_1218">GSGS-peptide数据</a>：来自MR121-GSGS-W肽的Gromacs模拟的仿真数据。更多信息请参考文档</li>
<li><a href="https://simtk.org/frs?group_id=513#pack_1416">Tica数据</a>：TICA模块输入所需的两个距离轨迹</li>
</ul>