Introduction and interests

[Bernardo Boatini]

Dear Mentor,

My name is Bernardo, and I am currently pursuing an MSc degree at the Federal University of Rio Grande do Sul - UFRGS (Brazil), specializing in active matter modeling and experiments applied to biological physics. I am writing to express my interest in the intern program offered by your esteemed institution.

In my research, I have focused on studying collective behavior, tissue mechanics, morphogenic dynamics, and other related topics. For my final thesis, I analyzed data from an MD implementation of tissue dynamics, which has helped me develop a strong understanding of molecular dynamics simulations.

I was delighted to discover the MDAnalysis library, which I believe will greatly enhance my ability to analyze data in my models. While working on my own implementations in numpy, I faced some challenges in studying order parameters and MSD patterns. I am keen to contribute to MDAnalysis to further develop my MD data processing skills and work collaboratively with the community to enhance the library. 

I am particularly interested in implment and exploring new types of measures, as suggested by Project 4. Furthermore, I have a keen interest in working with machine learning applied to molecular dynamics analysis. 

I would appreciate some guidance on how to get started with the program. Specifically, I would be grateful for any theoretical and practical guidance that you can offer me to help me get up to speed with your organization's projects and methodologies.

Thank you for your time and consideration.

Best regards,

Bernardo

[Oliver Beckstein]

Hi Bernardo,

welcome to MDAnalysis!

MDAnalysis is a Python package for the analysis of computer simulations of systems at the atomic scale. We have a few introductory videos that can give you an idea of what problems MDAnalysis is solving https://www.mdanalysis.org/pages/learning_MDAnalysis/#introductory . 

The best way to get started is to get your hands dirty following the MDAnalysis User Guide:

https://userguide.mdanalysis.org/stable/index.html

I would suggest starting with installing the MDAnalysis package (see https://userguide.mdanalysis.org/stable/installation.html) and going through the Quick Start Guide (https://userguide.mdanalysis.org/stable/examples/quickstart.html). Other sections of the User Guide go in much more details about the different capabilities of MDAnalysis.

Once you are a bit familiar with the MDAnalysis package, you can look at the sections of the User Guide explaining how to contribute:

https://userguide.mdanalysis.org/stable/contributing.html

There are detailed explanations on how to setup a developer environment (https://userguide.mdanalysis.org/stable/contributing_code.html) and how to contribute to the MDAnalysis codebase. This is a great starting point to start contributing to MDAnalysis and trying to solve some of the open issues.

Our blog post https://www.mdanalysis.org/2023/02/22/gsoc2023/ is the starting point for all GSoC 2023 things and we have a FAQ https://github.com/MDAnalysis/mdanalysis/wiki/GSoC-FAQ

On Feb 24, 2023, at 2:08 PM, Bernardo Boatini <b.boa...@gmail.com> wrote:

Dear Mentor,

My name is Bernardo, and I am currently pursuing an MSc degree at the Federal University of Rio Grande do Sul - UFRGS (Brazil), specializing in active matter modeling and experiments applied to biological physics. I am writing to express my interest in the intern program offered by your esteemed institution.

In my research, I have focused on studying collective behavior, tissue mechanics, morphogenic dynamics, and other related topics. For my final thesis, I analyzed data from an MD implementation of tissue dynamics, which has helped me develop a strong understanding of molecular dynamics simulations.

I was delighted to discover the MDAnalysis library, which I believe will greatly enhance my ability to analyze data in my models. While working on my own implementations in numpy, I faced some challenges in studying order parameters and MSD patterns. I am keen to contribute to MDAnalysis to further develop my MD data processing skills and work collaboratively with the community to enhance the library. 

To get familiar with MDAnalysis I suggest you try to implement some of your analysis using the library. For instance, the msd module https://docs.mdanalysis.org/stable/documentation_pages/analysis/msd.html can compute MSD and diffusion.

I am particularly interested in implment and exploring new types of measures, as suggested by Project 4. Furthermore, I have a keen interest in working with machine learning applied to molecular dynamics analysis. 

Learn to use the existing code, look at the existing code, get familiar with writing analysis tools with AnalysisBase https://userguide.mdanalysis.org/stable/examples/analysis/custom_trajectory_analysis.html

Best wishes,

Oliver

I would appreciate some guidance on how to get started with the program. Specifically, I would be grateful for any theoretical and practical guidance that you can offer me to help me get up to speed with your organization's projects and methodologies.

Thank you for your time and consideration.

Best regards,

Bernardo

--
GSoC 2023: Read https://www.mdanalysis.org/2023/02/22/gsoc2023/
Our FAQ: https://github.com/MDAnalysis/mdanalysis/wiki/GSoC-FAQ
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--

Oliver Beckstein (he/his/him)

email: orbe...@mdanalysis.org
twitter: @orbeckst

GitHub: @orbeckst

MDAnalysis – a NumFOCUS fiscally sponsored project

https://www.mdanalysis.org/