deploy: 5c51e12

_sources/domhmm.rst.txt

@@ -24,6 +24,11 @@ domhmm
 Installation instructions
 =========================
 
+The latest version of domhmm can be installed using the following:
+
+.. code-block:: bash
+
+    pip install domhmm
 
 The source code of domhmm can be installed using the following:
 
@@ -34,7 +39,7 @@ The source code of domhmm can be installed using the following:
 .. _`domhmm authors`:
    https://github.com/BioMemPhys-FAU/domhmm/blob/main/AUTHORS.md
 
-.. |domhmm_latest| image:: https://img.shields.io/badge/latest-unavailable-inactive.svg
+.. |domhmm_latest| image:: https://img.shields.io/badge/latest-passed-green.svg
    :alt: domhmm develop CI status
    :target: https://github.com/MDAnalysis/MDAKits/actions
 

_sources/mdakits.rst.txt

@@ -378,7 +378,7 @@ Each of the MDAKits in the following table links to a page with more details abo
 .. _`domhmm authors`:
    https://github.com/BioMemPhys-FAU/domhmm/blob/main/AUTHORS.md
 
-.. |domhmm_latest| image:: https://img.shields.io/badge/latest-unavailable-inactive.svg
+.. |domhmm_latest| image:: https://img.shields.io/badge/latest-passed-green.svg
    :alt: domhmm develop CI status
    :target: https://github.com/MDAnalysis/MDAKits/actions
 

domhmm.html

@@ -171,7 +171,7 @@
 <div class="line-block">
 <div class="line">* <a class="reference external" href="https://doi.org/10.1016/bs.mie.2024.03.006">https://doi.org/10.1016/bs.mie.2024.03.006</a></div>
 </div>
-<div class="line">🧪 <strong>Tests (latest):</strong> <a class="reference external" href="https://github.com/MDAnalysis/MDAKits/actions"><img alt="domhmm develop CI status" src="https://img.shields.io/badge/latest-unavailable-inactive.svg" /></a></div>
+<div class="line">🧪 <strong>Tests (latest):</strong> <a class="reference external" href="https://github.com/MDAnalysis/MDAKits/actions"><img alt="domhmm develop CI status" src="https://img.shields.io/badge/latest-passed-green.svg" /></a></div>
 <div class="line">🧪 <strong>Tests (develop):</strong> <a class="reference external" href="https://github.com/MDAnalysis/MDAKits/actions"><img alt="domhmm develop CI status" src="https://img.shields.io/badge/develop-passed-green.svg" /></a></div>
 <div class="line"><strong>Description:</strong></div>
 <div class="line"><a href="#id2"><span class="problematic" id="id3">*</span></a>TL;DR: DomHMM provides an automated workflow to identify liquid-ordered (Lo) domains from Molecular Dynamics simulations of bio-membranes. :-) Nano- and microdomains in lipid membranes are of great interest for understanding biological processes such as small molecule binding and signal transduction. Molecular Dynamics (MD) present a powerful tool for studying membranes with various lipid compositions at different levels of resolution. However, detecting these domains can be challenging, as most workflows are described in papers without available or maintained implementations. The MDAKit DomHMM faciliates the analysis of domains in your simulation trajectories by providing an automated workflow for the detection of lateral heterogeneities (i.e., liquid-ordered domains). It is a versatile tool to handle different use case scenarios, such as simulations of asymmetric membranes or membranes including small proteins. It utilizes therefore unsupervised machine learning algorithms, including Gaussian Mixture Models and Gaussian-based Hidden Markov Models, to detect ordered lipids based on their structural properties. Identified lipids are then clustered into domains using spatial autocorrelation analysis.</div>
@@ -181,6 +181,10 @@
 </ul>
 <section id="installation-instructions">
 <h2>Installation instructions<a class="headerlink" href="#installation-instructions" title="Link to this heading"></a></h2>
+<p>The latest version of domhmm can be installed using the following:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>domhmm
+</pre></div>
+</div>
 <p>The source code of domhmm can be installed using the following:</p>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>git+https://github.com/BioMemPhys-FAU/domhmm@main
 </pre></div>

mdakits.html

@@ -293,7 +293,7 @@ <h1>Registry of MDAnalysis Toolkits (MDAKits)<a class="headerlink" href="#regist
 <tr class="row-even"><td><p><a class="reference internal" href="domhmm.html#domhmm"><span class="std std-ref">domhmm</span></a></p></td>
 <td><p>membranes, molecular dynamics, nanodomains, microdomains, machine learning</p></td>
 <td><p><a class="reference external" href="https://github.com/BioMemPhys-FAU/domhmm/blob/main/AUTHORS.md">domhmm authors</a></p></td>
-<td><p><a class="reference external" href="https://github.com/MDAnalysis/MDAKits/actions"><img alt="domhmm develop CI status" src="https://img.shields.io/badge/latest-unavailable-inactive.svg" /></a> <a class="reference external" href="https://github.com/MDAnalysis/MDAKits/actions"><img alt="domhmm develop CI status" src="https://img.shields.io/badge/develop-passed-green.svg" /></a></p></td>
+<td><p><a class="reference external" href="https://github.com/MDAnalysis/MDAKits/actions"><img alt="domhmm develop CI status" src="https://img.shields.io/badge/latest-passed-green.svg" /></a> <a class="reference external" href="https://github.com/MDAnalysis/MDAKits/actions"><img alt="domhmm develop CI status" src="https://img.shields.io/badge/develop-passed-green.svg" /></a></p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="openmm-mdanalysis-reporter.html#openmm-mdanalysis-reporter"><span class="std std-ref">openmm-mdanalysis-reporter</span></a></p></td>
 <td><p>OpenMM, Reporters</p></td>