Marc Siggel

Postdoc @embl @EMBLHamburg | former PhD at @MPIbp

[Marc Siggel @MSiggel]

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 beginning🤩 #AlphaFold #cryoEM

[Jan Kosinski @jankosinski]

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: https://t.co/mCLg0hEQFr

[Jan Kosinski @jankosinski]

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 https://t.co/hph403KQCV

[bioRxiv Biophysics @biorxiv_biophys]

Helfrich Monte Carlo Flexible Fitting: physics-based, data-driven cell-scale simulations https://t.co/s2nqPoBZuz #biorxiv_biophys

[Marc Siggel @MSiggel]

Check out our new preprint!🚨
The all-in-one software solution Mosaic which we ship with this preprint now available on github as well!

https://t.co/YeQG3axTqU

[Weria Pezeshkian @WPezeshkian]

New collaborative preprint, Helfrich Monte Carlo Flexible Fitting: physics-based, data-driven cell-scale simulations. By Valentin J. Maurer @jankosinski @MSiggel
https://t.co/utDAV7prdT

[Weria Pezeshkian @WPezeshkian]

New collaborative preprint, Helfrich Monte Carlo Flexible Fitting: physics-based, data-driven cell-scale simulations. By Valentin J. Maurer @jankosinski @MSiggel
https://t.co/utDAV7prdT

[Google DeepMind @GoogleDeepMind]

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. 🧬

[Matt Sikora @BioPhysMatt]

Worried about your supercomputer electricity bill⚡️
We got your back!
Model your glycans in minutes with #GlycoSHIELD! Amazing collab w/ @cyril_hanus & Shang-Te Danny Hsu, now in @CellCellPress
https://t.co/0wlhUINvYx
@MCB_UJ @MPIbp @maxplanckpress @Inserm @AcadSinica #glycotime

[@[email protected] @_mischi]

This has been long in the making. Enough for me to have had my fingers in the code back in academia!

[@[email protected] @_mischi]

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!

https://t.co/KN6dkfmO43
https://t.co/qmKbjdDxfm

[Weria Pezeshkian @WPezeshkian]

I have an open PhD position.
If you are looking for a biomoldeing PhD position, this is for you.

https://t.co/ztguJ7e2Ew

[Jan Kosinski @jankosinski]

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 screenshots👇
https://t.co/Of8yShkGZ2

[Marc Siggel @MSiggel]

We also added an extensive tutorial to the user guide.📚 🤓
Head over to the quick start guide for all the details:
https://t.co/CrktyHDy2W

[Marc Siggel @MSiggel]

PyTME is finally out in Software X! 🖥️
If you've always wanted to try template matching on your cryo-ET data, now is a great time to start! ⏩
PyTME is fast, runs on multiple CPUs and GPUs, automatically optimizes RAM usage, and, and, and 🚀🚀
#teamtomo
https://t.co/dkoY4mPvAZ

[Matt Sikora @BioPhysMatt]

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 ☕️
https://t.co/3gE0dANeuB
Deadline 06.02!

[Weria Pezeshkian @WPezeshkian]

Our FreeDTS (software) work finally got published in Nat. Commune.
Exciting new features are under development and will be released soon.
https://t.co/adZsK8jg1J

[VanniLab @LabVanni]

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.

[Sergei Yakneen @SergeiIakhnin]

I’m 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.

[Jan Kosinski @jankosinski]

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: https://t.co/YfnHVc5KpC
Code &howto: https://t.co/e1Vt8exAHA

[Marc Siggel @MSiggel]

If you're into cryo-EM/ET and template matching check out our new library, pyTME! Faster ⏩(multi CPU and GPU), flexible, and easy to use! #teamtomo
https://t.co/fRJFsvmKF4

[bioRxiv @biorxivpreprint]

PyTME (Python Template Matching Engine): A fast, flexible, and multi-purpose template matching library for cryogenic electron microscopy data https://t.co/I7IzlalUiN #bioRxiv

[Google DeepMind @GoogleDeepMind]

Uncovering the causes of disease is one of the greatest challenges in genetics. 🧬

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. 🧵 https://t.co/ka19HXINjI

[Marc Siggel @MSiggel]

Great to see this finally out!

[Diz-Muñoz Lab @diz_lab]

🚨 New paper alert!! 🚨 Great work lead by @EwaSitarska on how curvature sensing proteins help cells to navigate in complex environments and to avoid bumping into obstacles! 👇

https://t.co/f5D9REIlM3