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Reposted by Christian Dallago

Stephan Hacker @stephanhacker2.bsky.social · 9d

Great talk by @machine.learning.bio at the 5th Virtual @chembiotalks.bsky.social. He talked about the use of #MachineLearning and #BigData to address biological questions. Cool insights into both predicting functions and designing proteins
ieeexplore.ieee.org/document/947...
arxiv.org/abs/2503.00710

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning

Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models (LMs) taken from Natural Language Processing (NLP). These LMs reach for new pred...

ieeexplore.ieee.org

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Reposted by Christian Dallago

Nature Methods @natmethods.nature.com · 20d

GPU-accelerated MMseqs2 offers tremendous speedup for homology retrieval, protein structure prediction with ColabFold, and protein structure search with Foldseek. @martinsteinegger.bsky.social @milot.bsky.social @machine.learning.bio

www.nature.com/articles/s41...

GPU-accelerated homology search with MMseqs2 - Nature Methods

Graphics processing unit-accelerated MMseqs2 offers tremendous speedups for homology retrieval from metagenomic databases, query-centered multiple sequence alignment generation for structure predictio...

www.nature.com

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Reposted by Christian Dallago

Arne Elofsson @bioinfo.se · 28d

podcasts.apple.com/us/podcast/f...

From AlphaFold to MMseqs2-GPU: How AI is Accelerating Protein Science

Podcast Episode · NVIDIA AI Podcast · 09/10/2025 · 35m

podcasts.apple.com

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Reposted by Christian Dallago

Stephan Hacker @stephanhacker2.bsky.social · Jul 16

Looking forward to hearing about the potential of machine learning for #Biology and #DrugDiscovery from an industry perspective. Register for the Virtual @chembiotalks.bsky.social to hear the perspective of Chris Dallago (@machine.learning.bio) from Nvidia.
#ChemBio #Chemsky #ML #MachineLearning

Virtual ChemBioTalks @chembiotalks.bsky.social · Jul 16

The third talk of the 5th Virtual ChemBioTalks will be given by Chris Dallago (@machine.learning.bio). He will talk about the research at NVIDIA into “Industrial BioML: the coming of age of machine learning for biology”.

Make sure to register for free: https://cvent.me/G1geWW

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Christian Dallago @machine.learning.bio · Jul 16

I still feel criminal for the handle but the manuscript embodies it well.

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Christian Dallago @machine.learning.bio · Jul 15

Moore’s law applied to speed not accuracy. I don’t think fundamentally the discoveries we are after are entirely dependent on speed.

I think the better law here is garbage in garbage out.

In that sense, you can wait for better data/curation, but it’s also fun to take destiny in your own hands :)

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Reposted by Christian Dallago

César de la Fuente @delafuentelab.bsky.social · Jul 14

(1/5) Venoms are a vast, largely untapped library of bioactive molecules—and our new paper in @natcomms.nature.com ‬ @natprot.nature.com reveals just how powerful they can be. 🐍⚡️

Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence - Nature Communications

Researchers used artificial intelligence to mine global venom proteomes and discovered novel peptides with antimicrobial activity. Several candidates showed efficacy against drug-resistant bacteria in...

www.nature.com

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Reposted by Christian Dallago

César de la Fuente @delafuentelab.bsky.social · Jul 11

Excited to have participated in the 2025 Symposium on Generative AI in Molecule Discovery in beautiful Munich, along with amazing scientists and colleagues @machine.learning.bio, Francesca Grisoni, ‪@ewaszczurek.bsky.social‬‬, @fabiantheis.bsky.social and more... 🔬🤖 events.hifis.net/event/2015/

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Reposted by Christian Dallago

Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · Jul 7

Folddisco finds similar (dis)continuous 3D motifs in large protein structure databases. Its efficient index enables fast uncharacterized active site annotation, protein conformational state analysis and PPI interface comparison. 1/9🧶🧬
📄 www.biorxiv.org/content/10.1...
🌐 search.foldseek.com/folddisco

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Christian Dallago @machine.learning.bio · Jun 15

Thanks to @pkoo562.bsky.social , @kevinkaichuang.bsky.social and Ananthan, and all of CSHL' staff for the help bringing this volume out. Hopefully, we could inspire all those fantastic biologists to reach out to their computational friends to take the next leap in their scientific discoveries.

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Christian Dallago @machine.learning.bio · Jun 15

With contributions from fantastic colleagues @martinsteinegger.bsky.social , @mikeinouye.bsky.social, @jlistgarten.bsky.social , @ideasbyjin.bsky.social, @michael-heinzinger.bsky.social, and many more, the first CSHL volume on ML for Protein Science and Engineering is out: lnkd.in/dQdgGPpp

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Christian Dallago @machine.learning.bio · Jun 15

If only there was something like try/catch in every programming/scripting language ever :P

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Christian Dallago @machine.learning.bio · Jun 15

The maddening bit is UniProt offers a handy URL that resolves whatever query you pass to it to a list of hits www.uniprot.org/help/api_que...

Whenever I used to implement search bars I’d use my dbs as autocomplete but one hop to that API endpoint to catch whatever the user inputs 🤷‍♂️

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Reposted by Christian Dallago

Stephan Hacker @stephanhacker2.bsky.social · Jun 10

The final program is now online for the 5th Virtual @chembiotalks.bsky.social: web.cvent.com/event/60e9f3...

Looking forward to talks by Sarah O'Connor, Chengqi Yi, @machine.learning.bio, @cathleenzeymer.bsky.social, @kellychibale.bsky.social, Jennifer Prescher and @craigmcrews.bsky.social.

Virtual ChemBioTalks @chembiotalks.bsky.social · Jun 10

The registration link and program for the 5th Virtual ChemBioTalks are finally available! If you are interested in the field of Chemical Biology, make sure to register for this free, virtual event on September 30th, 2025!
cvent.me/G1geWW (1/4)
#Chemsky #ChemBio

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Christian Dallago @machine.learning.bio · Jun 3

@michael-heinzinger.bsky.social and I are seeking talented postdocs to support for the Marie Skłodowska-Curie Fellowship! Join our international AI+biology team, collaborate on protein design, and access top labs in the US & EU. Interested? Apply by July 15! Details: machine.learning.bio/news/msca

Marie Skłodowska-Curie Fellowship

PostDoc Opportunity in AI for Protein Science Marie Skłodowska-Curie Fellowship

machine.learning.bio

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Reposted by Christian Dallago

Ewa Szczurek @ewaszczurek.bsky.social · Apr 7

Save the date for the Helmholtz Munich AI for Health Symposium 2025, devoted to the topic of Generative AI in Molecule Discovery!

July 4, 2025
Helmholtz Munich Campus in Neuherberg, Germany

What now?
Register and submit abstracts (deadline May 2, 2025!)
events.hifis.net/event/2015/r...

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Reposted by Christian Dallago

Karsten Kreis @karstenkreis.bsky.social · Mar 4

📢📢 "Proteina: Scaling Flow-based Protein Structure Generative Models"

#ICLR2025 (Oral Presentation)

🔥 Project page: research.nvidia.com/labs/genair/...
📜 Paper: arxiv.org/abs/2503.00710
🛠️ Code and weights: github.com/NVIDIA-Digit...

🧵Details in thread...

(1/n)

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Reposted by Christian Dallago

Karsten Kreis @karstenkreis.bsky.social · Mar 4

🔸Proteina is a fantastic collaboration with wonderful colleagues at NVIDIA:

🔥 Tomas Geffner*, @kdidi.bsky.social*, Zuobai Zhang*, Danny Reidenbach, Zhonglin Cao, @jyim.bsky.social , Mario Geiger, @machine.learning.bio, Emine Kucukbenli, @arashv.bsky.social, @karstenkreis.bsky.social* 🔥

(10/n)

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Christian Dallago @machine.learning.bio · Jan 12

Big time

Joe Greener @jgreener64.bsky.social · Jan 10

Favourite paper of 2019

"Learning Protein Structure with a Differentiable Simulator" by Ingraham et al. (1/4)

openreview.net/forum?id=Byg...

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Christian Dallago @machine.learning.bio · Jan 8

Whelp

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Reposted by Christian Dallago

Vega Shah @dr-alphalyrae.bsky.social · Jan 3

A DNA language model based on multispecies alignment predicts the effects of genome-wide variants | Nature Biotechnology
www.nature.com/articles/s41...

A DNA language model based on multispecies alignment predicts the effects of genome-wide variants - Nature Biotechnology

A language model predicts the effects of genetic variants in the human genome.

www.nature.com

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Christian Dallago @machine.learning.bio · Dec 24

Not yet, waiting for them visas

Christian Dallago @machine.learning.bio · Dec 23

Thanks. Once in full steam, there will be (way!) more GPU MSA-kinda things. Can't wait!

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Christian Dallago @machine.learning.bio · Dec 23

Vielen Dank :) I'll never turn down luck, always in high demand!

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Christian Dallago @machine.learning.bio · Dec 23

Thanks :) Indeed, new territory for everyone involved, but glad to be laying the path for something that'll hopefully be repeatable and the best of both worlds!

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