Postdoc @embl @EMBLHamburg | former PhD at @MPIbp
Joined March 2018
- Tweets 253
- Following 321
- Followers 240
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Pinned Tweet
28 Oct 2021
The models were so complete that we could perform coarse-grained MD simulations including the double membrane with ~100k lipids, and approximately 13.5 Million particles! So much to learn from this massive system. This is only the beginningš¤© #AlphaFold #cryoEM
28 Oct 2021
We combined #AlphaFold and #cryoEM to build a new model of the nuclear pore complex, the largest complex in the human cell!
The structure covered by the model is 15x bigger than the human ribosome and 2x bigger than old nuclear pore models. 1/7
Read how: biorxiv.org/content/10.1101/ā¦
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Marc Siggel retweeted
30 May 2025
New method toward modeling cells and viruses! HMFF enables integrative membrane modeling and simulation guided by electron microscopy data. Created by Valentin Maurer and @MSiggel @EMBLHamburg @CssbHamburg, in collaboration with @WPezeshkian lab biorxiv.org/content/10.1101/ā¦
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Marc Siggel retweeted
29 May 2025
Helfrich Monte Carlo Flexible Fitting: physics-based, data-driven cell-scale simulations biorxiv.org/content/10.1101/ā¦ #biorxiv_biophys
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29 May 2025
Check out our new preprint!šØ
The all-in-one software solution Mosaic which we ship with this preprint now available on github as well!
github.com/KosinskiLab/mosaiā¦
29 May 2025
New collaborative preprint, Helfrich Monte Carlo Flexible Fitting: physics-based, data-driven cell-scale simulations. By Valentin J. Maurer @jankosinski @MSiggel
biorxiv.org/content/10.1101/ā¦
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Marc Siggel retweeted
29 May 2025
New collaborative preprint, Helfrich Monte Carlo Flexible Fitting: physics-based, data-driven cell-scale simulations. By Valentin J. Maurer @jankosinski @MSiggel
biorxiv.org/content/10.1101/ā¦
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Marc Siggel retweeted
9 Oct 2024
Huge congratulations to @DemisHassabis and John Jumper on being awarded the 2024 Nobel Prize in Chemistry for protein structure prediction with #AlphaFold, along with David Baker for computational protein design.
This is a monumental achievement for AI, for computational biology, and science itself. š§¬
9 Oct 2024
BREAKING NEWS
The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker āfor computational protein designā and the other half jointly to Demis Hassabis and John M. Jumper āfor protein structure prediction.ā
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Marc Siggel retweeted
29 Feb 2024
Worried about your supercomputer electricity billā”ļø
We got your back!
Model your glycans in minutes with #GlycoSHIELD! Amazing collab w/ @cyril_hanus & Shang-Te Danny Hsu, now in @CellCellPress
tinyurl.com/bdhuzbnu
@MCB_UJ @MPIbp @maxplanckpress @Inserm @AcadSinica #glycotime
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Marc Siggel retweeted
29 Feb 2024
This has been long in the making. Enough for me to have had my fingers in the code back in academia!
29 Feb 2024
Worried about your supercomputer electricity billā”ļø
We got your back!
Model your glycans in minutes with #GlycoSHIELD! Amazing collab w/ @cyril_hanus & Shang-Te Danny Hsu, now in @CellCellPress
tinyurl.com/bdhuzbnu
@MCB_UJ @MPIbp @maxplanckpress @Inserm @AcadSinica #glycotime
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Marc Siggel retweeted
3 Feb 2024
Vision Pro is cool and all, but have you ever spent time searching for that format error in your YAML file? Apple just open sourced their new type-safe configuration language Pkl. Define once, and safely render into many formats!
pkl-lang.org/blog/introducinā¦
github.com/apple/pkl
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Marc Siggel retweeted
2 Feb 2024
I have an open PhD position.
If you are looking for a biomoldeing PhD position, this is for you.
candidate.hr-manager.net/Appā¦
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Marc Siggel retweeted
28 Jan 2024
The final version of the PyTME paper published in @SoftXJournal! PyTME enables fast CPU and GPU-based template matching in #cryoET and fitting in #cryoEM. More in the thread with plenty of screenshotsš
sciencedirect.com/science/arā¦
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27 Jan 2024
PyTME is finally out in Software X! š„ļø
If you've always wanted to try template matching on your cryo-ET data, now is a great time to start! ā©
PyTME is fast, runs on multiple CPUs and GPUs, automatically optimizes RAM usage, and, and, and šš
#teamtomo
sciencedirect.com/science/arā¦
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27 Jan 2024
We also added an extensive tutorial to the user guide.š š¤
Head over to the quick start guide for all the details:
kosinskilab.github.io/pyTME/ā¦
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Marc Siggel retweeted
24 Jan 2024
Always wanted to run simulations of extracellular matrix, but didn't know where to start? Search no more! Exciting postdoc position @MCB_UJ in our #dioscuri lab, lots of MD sims, great experimental collabs, and, as always, good coffee āļø
tinyurl.com/4v5ahkjn
Deadline 06.02!
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Marc Siggel retweeted
17 Jan 2024
Our FreeDTS (software) work finally got published in Nat. Commune.
Exciting new features are under development and will be released soon.
nature.com/articles/s41467-0ā¦
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We are looking for 1 PhD and 1 Postdoc to work on MD simulations of lipid metabolism funded by @snsf_ch. Interviews will start in Jan. Excellent salary, resources, colleagues and collaborators. Plus the science is great (but I am biased...)! Contact me by email if interested.
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Marc Siggel retweeted
31 Oct 2023
Iām incredibly proud to share this joint work by @IsomorphicLabs and @GoogleDeepMind on the latest version of AlphaFold, demonstrating SOTA on a wide variety of tasks, including protein-ligand structure, nucleic acids, PPIs, and PTMs.
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Marc Siggel retweeted
25 Oct 2023
Super fast and versatile toolbox for both single-particle #cryoEM and in-situ #teamtomo cryo-ET! Our new pyTME library consolidates particle picking/structure fitting/template matching in a single framework.
Preprint: biorxiv.org/content/10.1101/ā¦
Code &howto: github.com/KosinskiLab/pyTME
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25 Oct 2023
If you're into cryo-EM/ET and template matching check out our new library, pyTME! Faster ā©(multi CPU and GPU), flexible, and easy to use! #teamtomo
kosinskilab.github.io/pyTME/
25 Oct 2023
PyTME (Python Template Matching Engine): A fast, flexible, and multi-purpose template matching library for cryogenic electron microscopy data biorxiv.org/cgi/content/shorā¦ #bioRxiv
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Marc Siggel retweeted
19 Sep 2023
Uncovering the causes of disease is one of the greatest challenges in genetics. š§¬
To help advance this, we created AlphaMissense: an AI model classifying missense variants - or genetic changes affecting proteins.
Here's how it can help scientists. š§µ dpmd.ai/alphamissense-blog
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14 Sep 2023
Great to see this finally out!
14 Sep 2023
šØ New paper alert!! šØ Great work lead by @EwaSitarska on how curvature sensing proteins help cells to navigate in complex environments and to avoid bumping into obstacles! š
rdcu.be/dl7DP
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