Lorenz Lamm

PhD Student at Helmholtz AI || AI for Cryo-Electron Tomography

[Lorenz Lamm @LorenzLamm]

„My finger hurts from clicking all those membrane proteins! 😩”
– A sentence you will never have to say again.

Check out the preprint about MemBrain 💻🧠: Our #DeepLearning -aided tool for membrane protein detection in cryo-ET.
https://t.co/Jhpmvx8fM3

🧵How it works: 🧵 (1/N)

[Rushin Gindra @rushin_gindra]

1/7🎉 Introducing Phoenix: generative AI predicting spatially resolved gene expression from routine H&E slides-enabling virtual spatial-omics. Zero-shot. Across cancers, organs & species.
Huge thanks to my co-first @TranManuel & all collaborators! 🙌
📜: https://t.co/MtmnyHfWZn

[Florent Waltz @FlorentWaltz]

You want to start tomography? Solve structures inside cells? Reach Nyquist😳?
We have a website for you! https://t.co/ulvbbhEY6d
You'll find a tutorial on how to reconstruct tomograms, pick particles and do subtomo averaging, using different software!
Hope it will be useful !

[Fabian Isensee @FabianIsensee1]

Excited to share nnInteractive: The nnU-Net moment for 3D Interactive Segmentation! Supports points, scribbles, boxes, & a new lasso prompt for full 3D masks from 2D inputs. Check it out: https://t.co/MyNQyUDd4x
https://t.co/waDcltB9dG
https://t.co/uWoqHI3Ruf

[Jianxu Chen @JianxuChen]

A new pre-print for LSFM lovers in the bioimaging community: https://t.co/GJb6u7C46a w. python + napari. We would love to hear your feedbacks. Thanks for the Peng Lab in Helmholtz Munich and the Huisken Lab in Göttingen for having us along the journey in this great collaboration.

[Sagar @CryoSagar]

Hey #teamtomo checkout our team science approach to #cellbio #cryoET

I can’t thank @bengeliscious enough for this one 😍😍

Awesome team science from @MPI_Biochem @biozentrum @thermosciEMSpec and more

Signing off Twitter with a good one

https://t.co/r4tT7jTUgW

[Sophia J. Wagner @sophiajwagner]

Excited to share TITAN, a multimodal foundation model for pathology trained on >330k WSIs, synthetic captions, and reports🔬⚡
co-lead w @TongDing99 @GreatAndrew90 @richardjchen
Thanks to @AI4Pathology @p_tingying!

Preprint: https://t.co/LpgmNlbvMa
Model: https://t.co/gYJxLcjKiS

[Matt Johnson @Johnson_mattp]

🥳New cryo tomography Preprint ☀️🌱🔬Molecular architecture of thylakoid membranes within intact spinach chloroplasts.

https://t.co/ePKx2jhRYD

Proud to be part of this great work with @bengeliscious @woj_wie @LorenzLamm @DrLornaMalone @whjwood @PPS_UoS

[Florian Kofler @neuronflow]

We present MultiOrg: an #organoid dataset tailored for #object_detection tasks with #uncertainty quantification. Over 400 high-resolution 2D #microscopy images and multi-expert annotations of more than 60,000 organoids.
Paper: https://t.co/39WjGkSVF4
Data: https://t.co/64vBOSvPGi

[Francesco Padovani @frank_pado]

SpotMAX, our software tool for analysing multi-dimensional microscopy data, is finally out! 🎉 And conveniently, I just presented it at the #I2K conference 😀
A multi-year-long effort of many great collaborators and users. But what can SpotMAX do? A small thread

[Princeton Materials Institute @PrincetonMSE]

Tingying Peng (@p_tingying) of @HelmholtzMunich presented MemBrain v2, “an end-to-end tool for analysis of membranes in cryo-electron tomography” #FEMPL3

[Tingying Peng @p_tingying]

I’m thrilled to introduce MemBrain V2(https://t.co/YLuu6oKEqt), our latest research tool developed by @LorenzLamm and co-supervised by @bengeliscious, right here at the beautiful Princeton campus. It’s exciting to see how widely it’s being adopted by the community!

[Valentin Koch @ValentinKoch_]

1/ 🧵Introducing UNICORN,🦄 the first #AI model for integrating multi-stain #histopathology images for classification, designed to tackle missing data during both training and inference. Great colab between @HelmholtzMunich & @TU_Muenchen German Heart Centre! the architecture ⬇️

[Marten Chaillet (@martenchaillet.bsky.social) @ChailletMarten]

Really happy to share that the last chapter of my submitted phd thesis is already on biorxiv!🥳
Using a tophat transform, I made template matching more precise, allowing automated annotation with little false positives! #teamtomo
https://t.co/Y7K8l3fSCk

[Florent Waltz @FlorentWaltz]

Super excited to share our latest work on the native in-cell organization of the mitochondrial respiratory chain 🥳
Using cryo-electron tomography🔬, we show how the respiratory complexes (and other complexes) are organized inside native mitochondria! 
https://t.co/cxHl1j20CJ

[Marten Chaillet (@martenchaillet.bsky.social) @ChailletMarten]

I just made a website for pytom-match-pick using the slick mkdocs-material theme: https://t.co/hovnhyGRNo

Some more updates following soon😮

[Tomáš Chobola @ifelsetom]

⚡️ Excited to announce that CoLIE has been accepted to #ECCV2024!

CoLIE uses a neural implicit representation to enhance low-light images according to the Retinex theory.

@p_tingying
@ja_schnabel
@eccvconf

Paper: https://t.co/EHwJEJpavg
Code: https://t.co/K2ioykLMKL

[Open Life Science AI @OpenlifesciAI]

The future is bright! We're going to make amazing discoveries about how cells work, and that means better understanding of health, disease, and even how we age!
Thanks to @ErmelUtz , @LorenzLamm , @bengeliscious for their amazing work.

Paper: https://t.co/O7ZSIRDlMd

[biohub @biohub]

It can take months to annotate a set of tomograms captured by #CryoET manually.

@ErmelUtz adapted @lorenzlamm + @bengeliscious’ deep-learning algorithm MemBrain to annotate cell membranes in over 13k tomograms in just 3.5 days
https://t.co/on1WyjDsPt

[Chan Zuckerberg Initiative @ChanZuckerberg]

These are 3D images of the inner workings of human cells. Because they are so detailed, each set can take months to analyze.

To accelerate discovery, #CZImagingInstitute scientists applied @lorenzlamm + @bengeliscious’ AI technique that could analyze 13k+ images in just 3.5 days

[CCP-EM @ccp_em]

Recorded talks from the 2024 CCP-EM Spring Symposium are available here... https://t.co/BPXLXQ9nK8