From c9c7079eceb6382d66a2ccfdaa8e367af13fe1a3 Mon Sep 17 00:00:00 2001 From: Marius Trollmann Date: Fri, 6 Sep 2024 16:27:18 +0200 Subject: [PATCH 1/5] MDAKit registration: DomHMM --- mdakits/domhmm/metadata.yaml | 121 +++++++++++++++++++++++++++++++++++ 1 file changed, 121 insertions(+) create mode 100644 mdakits/domhmm/metadata.yaml diff --git a/mdakits/domhmm/metadata.yaml b/mdakits/domhmm/metadata.yaml new file mode 100644 index 00000000..f6bfe10c --- /dev/null +++ b/mdakits/domhmm/metadata.yaml @@ -0,0 +1,121 @@ +# TEMPLATE MDAKit file +# -------------------- +# +# Please replace ALL entries with appropriate content for YOUR MDAKit. +# Below we use the placeholder GH_HOST_ACCOUNT for the GitHub account where +# the source code repository is held, typically your username or the +# organization that you're part off. +# MYPROJECT is the name of your project (the repository name and here +# we assume that this is also the PyPi/conda package name) whereas +# MYPACKAGE is how you import it in python. +# +# See https://mdakits.mdanalysis.org/add.html for more information. +# +#------------------------------------------------------------ +# Required entries +#------------------------------------------------------------ +## str: name of the project (the respository name) +project_name: domhmm + +## List(str): a link to the authors file (preferred) or a list of authors +authors: + - https://github.com/BioMemPhys-FAU/domhmm/blob/main/AUTHORS.md + +## List(str): a list of maintainers +## Please note these _must_ be GitHub handles +## The maintainers will be tagged in issues if their MDAKit is failing. +maintainers: + - m-a-r-i-u-s + - yusuferentunc + - biomemphys + +## str: a free form description of the mdakit +description: + DomHMM provides an automated workflow to identify liquid-ordered (Lo) domains from Molecular Dynamics simulations of bio-membranes. + +## List(str): a list of keywords which describe the mdakit +keywords: + - membranes + - molecular dynamics + - nanodomains + - microdomains + +## str: the license the mdakit falls under +## See https://spdx.org/licenses/ for valid license specifiers +license: GPL-2.0-or-later + +## str: the link to the project's code +## Please note that this is not limited to GitHub! Can be Gitlab, etc.. +project_home: https://github.com/BioMemPhys-FAU/domhmm + +## str: the link to the project's documentation +documentation_home: https://domhmm.readthedocs.io + +## str: the type of documentation available [UserGuide, API, README] +documentation_type: UserGuide + API + +## List(str): a list of commands to use when installing the mdakit from its +## source code. +src_install: + - pip install git+https://github.com/BioMemPhys-FAU/domhmm@main + +## str: the package name used to import the mdakit +import_name: domhmm + +## str: a specification for the range of Python versions supported by this MDAKit +python_requires: ">=3.9" + +## str: a specification for the range of MDAnalysis versions supported by this MDAKit +mdanalysis_requires: ">=2.0.0" + +## List(str): a list of commands to use when attempting to run the MDAKit's tests +## If you package your tests inside your package then you can typically use the +## pytest --pyargs MYPACKAGE +## command as shown below. +## Otherwise you need to include commands to make the tests available. +## For example, if the tests are in the repository at the top level under `./tests`: +## First use `git clone latest` to either clone the top commit for "development code" checks or check out +## the latest tag for "latest release" checks. Then then run pytest: +## - git clone latest +## - pytest -v ./tests +## Feel free to ask for advice on your pull request! +run_tests: + - pytest --pyargs domhmm + +## List(str): a list of commands to use to install the necessary dependencies required +## to run the MDAKit's tests. +## The default below _might_ be sufficient or you might not even need MDAnalysisTests: +## make sure that it is appropriate for how you run tests. +test_dependencies: + - mamba install pytest + +## str: the organisation name the MDAKit falls under +project_org: BioMemPhys-FAU + +#------------------------------------------------------------ +# Optional entries +#------------------------------------------------------------ +## List(str): a list of commands to use when installing the latest +## release of the code. Note: only one installation method can currently +## be defined. We suggest using mamba where possible (e.g. +## mamba -c conda-forge install MYPROJECT +## for a conda package installation). +## Here we use a simple PyPi installation: +#install: +# - pip install MYPROJECT + +## str: the development status of the MDAKit +## See https://pypi.org/classifiers/ for development status classifiers. +development_status: Production/Stable + +## List(str) a list of publications to cite when using the MDAKit +## Links to scientific publications or stable URLs (typically of the form +## https://doi.org/ or to a preprint server) +publications: + - https://doi.org/10.1016/bs.mie.2024.03.006 + +## str: a link to the MDAKit's community (mailing list, github discussions, etc...) +community_home: https://github.com/BioMemPhys-FAU/domhmm/discussions/ + +## str: a link to the MDAKit's changelog +changelog: https://github.com/BioMemPhys-FAU/domhmm/blob/main/CHANGELOG.md From 24c8372ceb1787049d844ba5c240e877fcf8404d Mon Sep 17 00:00:00 2001 From: Marius <44572437+m-a-r-i-u-s@users.noreply.github.com> Date: Sat, 7 Sep 2024 12:17:03 +0200 Subject: [PATCH 2/5] Update metadata.yaml --- mdakits/domhmm/metadata.yaml | 85 +++++++++++++----------------------- 1 file changed, 31 insertions(+), 54 deletions(-) diff --git a/mdakits/domhmm/metadata.yaml b/mdakits/domhmm/metadata.yaml index f6bfe10c..0410300f 100644 --- a/mdakits/domhmm/metadata.yaml +++ b/mdakits/domhmm/metadata.yaml @@ -1,95 +1,77 @@ -# TEMPLATE MDAKit file +# DomHMM - Detect, Analyze, Understand # -------------------- -# -# Please replace ALL entries with appropriate content for YOUR MDAKit. -# Below we use the placeholder GH_HOST_ACCOUNT for the GitHub account where -# the source code repository is held, typically your username or the -# organization that you're part off. -# MYPROJECT is the name of your project (the repository name and here -# we assume that this is also the PyPi/conda package name) whereas -# MYPACKAGE is how you import it in python. +# TL;DR: DomHMM provides an automated workflow to identify liquid-ordered (Lo) domains from Molecular Dynamics simulations of bio-membranes. :-) # -# See https://mdakits.mdanalysis.org/add.html for more information. +# 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. +# More details about the method can be found here: https://doi.org/10.1016/bs.mie.2024.03.006. # #------------------------------------------------------------ # Required entries #------------------------------------------------------------ -## str: name of the project (the respository name) +## Name of the repository project_name: domhmm -## List(str): a link to the authors file (preferred) or a list of authors +## List of DomHMM's authors authors: - https://github.com/BioMemPhys-FAU/domhmm/blob/main/AUTHORS.md -## List(str): a list of maintainers -## Please note these _must_ be GitHub handles -## The maintainers will be tagged in issues if their MDAKit is failing. +## List of DomHMM's maintainers maintainers: - m-a-r-i-u-s - yusuferentunc - biomemphys -## str: a free form description of the mdakit +## What is DomHMM description: - DomHMM provides an automated workflow to identify liquid-ordered (Lo) domains from Molecular Dynamics simulations of bio-membranes. - -## List(str): a list of keywords which describe the mdakit + 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. + +## Keywords that relate to DomHMM keywords: - membranes - molecular dynamics - nanodomains - microdomains + - machine learning -## str: the license the mdakit falls under -## See https://spdx.org/licenses/ for valid license specifiers license: GPL-2.0-or-later -## str: the link to the project's code -## Please note that this is not limited to GitHub! Can be Gitlab, etc.. +## You can find DomHMM on our GitHub repository: project_home: https://github.com/BioMemPhys-FAU/domhmm -## str: the link to the project's documentation +## You can find the documentation of DomHMM here: documentation_home: https://domhmm.readthedocs.io -## str: the type of documentation available [UserGuide, API, README] documentation_type: UserGuide + API -## List(str): a list of commands to use when installing the mdakit from its -## source code. src_install: - pip install git+https://github.com/BioMemPhys-FAU/domhmm@main -## str: the package name used to import the mdakit import_name: domhmm -## str: a specification for the range of Python versions supported by this MDAKit python_requires: ">=3.9" -## str: a specification for the range of MDAnalysis versions supported by this MDAKit mdanalysis_requires: ">=2.0.0" -## List(str): a list of commands to use when attempting to run the MDAKit's tests -## If you package your tests inside your package then you can typically use the -## pytest --pyargs MYPACKAGE -## command as shown below. -## Otherwise you need to include commands to make the tests available. -## For example, if the tests are in the repository at the top level under `./tests`: -## First use `git clone latest` to either clone the top commit for "development code" checks or check out -## the latest tag for "latest release" checks. Then then run pytest: -## - git clone latest -## - pytest -v ./tests -## Feel free to ask for advice on your pull request! +## The repositiory of DomHMM includes some unit tests to ensure that the package runs as intended. Please note that we are using pytest to run the tests. run_tests: - pytest --pyargs domhmm - -## List(str): a list of commands to use to install the necessary dependencies required -## to run the MDAKit's tests. -## The default below _might_ be sufficient or you might not even need MDAnalysisTests: -## make sure that it is appropriate for how you run tests. + test_dependencies: - mamba install pytest -## str: the organisation name the MDAKit falls under +## Computational Biology - Department Biologie - Friedrich-Alexander-Universität Erlangen-Nürnberg project_org: BioMemPhys-FAU #------------------------------------------------------------ @@ -101,21 +83,16 @@ project_org: BioMemPhys-FAU ## mamba -c conda-forge install MYPROJECT ## for a conda package installation). ## Here we use a simple PyPi installation: +# More to come! #install: # - pip install MYPROJECT -## str: the development status of the MDAKit -## See https://pypi.org/classifiers/ for development status classifiers. development_status: Production/Stable -## List(str) a list of publications to cite when using the MDAKit -## Links to scientific publications or stable URLs (typically of the form -## https://doi.org/ or to a preprint server) publications: - https://doi.org/10.1016/bs.mie.2024.03.006 -## str: a link to the MDAKit's community (mailing list, github discussions, etc...) +# We welcome your feedback on the code or any other aspects of the project. :-) community_home: https://github.com/BioMemPhys-FAU/domhmm/discussions/ -## str: a link to the MDAKit's changelog changelog: https://github.com/BioMemPhys-FAU/domhmm/blob/main/CHANGELOG.md From d5987e66d7d9d9367d52ea27145c4a43ca46e957 Mon Sep 17 00:00:00 2001 From: Marius <44572437+m-a-r-i-u-s@users.noreply.github.com> Date: Tue, 10 Sep 2024 09:52:57 +0200 Subject: [PATCH 3/5] Update metadata.yaml --- mdakits/domhmm/metadata.yaml | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/mdakits/domhmm/metadata.yaml b/mdakits/domhmm/metadata.yaml index 0410300f..2d2852f0 100644 --- a/mdakits/domhmm/metadata.yaml +++ b/mdakits/domhmm/metadata.yaml @@ -27,9 +27,8 @@ maintainers: - biomemphys ## What is DomHMM -description: +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. From 40d5e0403e8c019cfcbd2c66b969eb94b73f6549 Mon Sep 17 00:00:00 2001 From: Marius <44572437+m-a-r-i-u-s@users.noreply.github.com> Date: Wed, 11 Sep 2024 14:08:06 +0200 Subject: [PATCH 4/5] Update metadata.yaml --- mdakits/domhmm/metadata.yaml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/mdakits/domhmm/metadata.yaml b/mdakits/domhmm/metadata.yaml index 2d2852f0..0ace3f8a 100644 --- a/mdakits/domhmm/metadata.yaml +++ b/mdakits/domhmm/metadata.yaml @@ -83,8 +83,9 @@ project_org: BioMemPhys-FAU ## for a conda package installation). ## Here we use a simple PyPi installation: # More to come! -#install: -# - pip install MYPROJECT +install: + - git clone latest + - pip install . development_status: Production/Stable From 94e51b5c305f4b01f300394b30249679a0b096ff Mon Sep 17 00:00:00 2001 From: Marius <44572437+m-a-r-i-u-s@users.noreply.github.com> Date: Thu, 12 Sep 2024 22:20:04 +0200 Subject: [PATCH 5/5] Update metadata.yaml --- mdakits/domhmm/metadata.yaml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/mdakits/domhmm/metadata.yaml b/mdakits/domhmm/metadata.yaml index 0ace3f8a..9d461168 100644 --- a/mdakits/domhmm/metadata.yaml +++ b/mdakits/domhmm/metadata.yaml @@ -83,9 +83,9 @@ project_org: BioMemPhys-FAU ## for a conda package installation). ## Here we use a simple PyPi installation: # More to come! -install: - - git clone latest - - pip install . +# install: +# - git clone latest +# - pip install . development_status: Production/Stable