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De$FDb delta 95 zcmZ2>ign*9R+a|Vsf-(0=3Sp$z1n}ewKrqX)fsNF diff --git a/_sources/domhmm.rst.txt b/_sources/domhmm.rst.txt index a47cbafb..5a676524 100644 --- a/_sources/domhmm.rst.txt +++ b/_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 diff --git a/_sources/mdakits.rst.txt b/_sources/mdakits.rst.txt index 48992f36..9ff287f0 100644 --- a/_sources/mdakits.rst.txt +++ b/_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 diff --git a/_static/css/theme.css b/_static/css/theme.css index 6843d97b..0f14f106 100644 --- a/_static/css/theme.css +++ b/_static/css/theme.css @@ -1,4 +1,4 @@ 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format("woff2"),url(fonts/Roboto-Slab-Bold.woff?bed5564a116b05148e3b3bea6fb1162a) format("woff");font-display:block} \ No newline at end of file diff --git a/domhmm.html b/domhmm.html index 55b833b3..7313ac45 100644 --- a/domhmm.html +++ b/domhmm.html @@ -171,7 +171,7 @@
* https://doi.org/10.1016/bs.mie.2024.03.006
-
🧪 Tests (latest): domhmm develop CI status
+
🧪 Tests (latest): domhmm develop CI status
🧪 Tests (develop): domhmm develop CI status
Description:
*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.
@@ -181,6 +181,10 @@

Installation instructions

+

The latest version of domhmm can be installed using the following:

+
pip install domhmm
+
+

The source code of domhmm can be installed using the following:

pip install git+https://github.com/BioMemPhys-FAU/domhmm@main
diff --git a/mdakits.html b/mdakits.html index 00402dcc..50b9065a 100644 --- a/mdakits.html +++ b/mdakits.html @@ -293,7 +293,7 @@

Registry of MDAnalysis Toolkits (MDAKits)

domhmm

membranes, molecular dynamics, nanodomains, microdomains, machine learning

domhmm authors

-

domhmm develop CI status domhmm develop CI status

+

domhmm develop CI status domhmm develop CI status

openmm-mdanalysis-reporter

OpenMM, Reporters

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