Žiga Avsec

Very excited to share our work at @GoogleDeepMind on missense variant pathogenicity prediction using AlphaMissense, new in @sciencemagazine doi.org/10.1126/scienc…. Long 🧵focused on more technical details. 1/

Thrilled to introduce AlphaGenome, our new DNA sequence model now available via our AlphaGenome API. Really excited to see how the scientific community uses AlphaGenome’s predictions to understand genome function, drive biological discoveries, develop new treatments, and more...

Excited to share #AlphaGenome, a start of our AlphaGenome named journey to decipher the regulatory genome! The model matches or exceeds top-performing external models on 24 out of 26 variant evaluations, across a wide range of biological modalities.1/6

Happy to introduce AlphaGenome, @GoogleDeepMind's new AI model for genomics. AlphaGenome offers a comprehensive view of the human non-coding genome by predicting the impact of DNA variations. It will deepen our understanding of disease biology and open new avenues of research.

This a really exciting leap forward for genomic sequence to activity gene regulation models. It is a genuine improvement over pretty much all SOTA models spanning a wide range of regulatory, transcriptional and post-transcriptional processes. 1/

I’m excited to co-host the new #AIxBio conference alongside @Avsecz, @ferruz_noelia, @pdhsu, @BenLehner, @ml19, @deboramarks, @p_tingying, @CarolineUhlerat at @wellcomegenome/ @sangerinstitute! We’ll focus on modellingz and designing DNA, RNA, proteins, and cells, as well as…

Excited to share our latest preprint, as part of ENCODE4, on a consensus variant-to-function (cV2F) score for functionally prioritizing variants for complex disease - led by Tabassum Fabiha and co-mentored with Alkes Price. biorxiv.org/content/10.110…

If AlphaFold was proof of AI’s potential, it is now also prelude – to a future of incredible progress, driven by AI, shaped by human ingenuity, and guided by a collective sense of responsibility and safety. Massive congrats to @demishassabis and John on winning the Nobel Prize!

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…

Really pleased to see DeepRVAT published. A new method for rare variant genetics by @Holtkamp_Eva & @brianfclarke in collab with @gagneurlab. I like to think of DeepRVAT as one network on top of another, harnessing variant annotations from bags of models- AlphaMissense and alike.

🧵 1/9 Delighted to announce that #DeepRVAT is out today in Nature Genetics! Here's a recap of our tweetorial from the preprint, with updates for some exciting new results. It's been a joy to work with @Holtkamp_Eva, as well as @gagneurlab and @OliverStegle.

Solving International Maths Olympiad (IMO) level problems has been a grand challenge for AI systems. Happy to share that a new solver (AlphaProof) developed by our team @GoogleDeepMind and our geometry solver (AlphaGeometry) were able to solve 4 out the 6 IMO 2024 problems!

Advanced mathematical reasoning is a critical capability for modern AI. Today we announce a major milestone in a longstanding grand challenge: our hybrid AI system attained the equivalent of a silver medal at this year’s International Math Olympiad!

New preprint: sequence-based models are very good at predicting human protein missense variants with an impact on function. Here we use AlphaFold2 models to infer mechanisms of effect of deleterious variants (stability, pockets and protein interfaces) biorxiv.org/content/10.110…