Projects
A FAIR workflow platform
FAIR stands for Findable, Accessible, Interoperable, Reuseable. By making research data available in a FAIR manner, researchers can make their data more useful! However, implementing FAIR principles is still challenging.
In this work, me and my collegues from Senckenberg implemented a workflow platform that can execute machine-actionable workflows. The resulting data is made available in a FAIR manner by implementing RO-Crates and FAIR Signposting. The platform code is open-source: Github
griesheim-transparent.de
https://griesheim-transparent.de is a platform designed to increasing transparency in local government for the citizens of Griesheim.
The platform indexes documents from the local government and makes them available through a search interface. It provides full-text search capabilities on resolutions, council meeting minutes, etc.
The goal is to empowers citizens by enabling easy access to important governmental documents and fostering greater community involvement.
Corax: A Split ergo keyboard
The Corax is a custom mechanical keyboard I designed and built from the ground up. It is fully programmable using the ZMK firmare, featuers a split and column-staggered layout, bluetooth, and hot-swappable switches.
The design of the PCB, 3D printed parts and the firmware are available on Github.
Molecular dynamics simulations of ion channels
DOI: 10.26083/tuprints-00018611
During my PhD, I focused on understanding the workings of ion channels, particularly HCN channels. These channels are essential in regulating heart rhythms and various neuronal processes in human.
I used molecular dynamics simulations to explore ion conductance properties and contributed to research related to channelopathies (diseases related to channel malfunctioning).
Weighted Histogram Analysis Method (WHAM)
wham --max 3.14,3.14 --min -3.14,-3.14 -T 300 --bins 100,100 --cyclic -f example/2d/metadata.dat
> Supplied WHAM options: Metadata=example/2d/metadata.dat, hist_min=[-3.14, -3.14], hist_max=[3.14, 3.14], bins=[100, 100] verbose=false, tolerance=0.000001, iterations=100000, temperature=300, cyclic=true
> Reading input files.
> 625 windows, 624262 datapoints
> Iteration 10: dF=0.389367172324539
> Iteration 20: dF=0.21450559607810152
(...)
> Iteration 620: dF=0.0000005800554892309461
> Iteration 630: dF=0.00000047424278621817084
> Finished. Dumping final PMF
(... pmf dump ...)
The Weighted Histogram Analysis Method (WHAM) is a fast implementation of WHAM written in Rust. It allows the calculation of multidimensional free energy profiles from umbrella sampling simulations. I wrote WHAM during my PhD because there was no polished implementation of WHAM that was able to utilize more than one CPU. This implementation is particularly well-suited for larger systems and and features additional error analysis features.