Jun Cheng
@s6juncheng
Computational Biology | Machine learning research scientist at @GoogleDeepMind
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
It's always great to look back on the year in a year-in-review blogpost with @JeffDean & James Manyika. It's been an amazingly productive year for us, doing awesome research, shipping products and advancing science - 2024 is going to be incredible! deepmind.google/discover/blog/…
Excited to launch our AlphaGenome API goo.gle/3ZPUeFX along with the preprint goo.gle/45AkUyc describing and evaluating our latest DNA sequence model powering the API. Looking forward to seeing how scientists use it! @GoogleDeepMind
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.
We are looking a PhD Student Researcher at Google DeepMind for 2025 summer! Strong publication record and technical skills on machine learning and genomics preferred. Need to be 80% for a few months. Team in London. Looking forward to hear from you!
It’s been an amazing last couple of weeks, hope you enjoyed our end of year extravaganza as much as we did! Just some of the things we shipped: state-of-the-art image, video, and interactive world models (Imagen 3, Veo 2 & Genie 2); Gemini 2.0 Flash (a highly performant and…
Nice work applying VEP to gene burden testing, bridging variant effect to gene functions.
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.
AlphaMissense predictions are now more easily accessible thanks to the great work of @emblebi! On AFDB you can also download per protein predictions.
To help scientists explore whether a genetic variant is likely pathogenic, and which regions of proteins are functionally important, we've integrated AlphaMissense data by @GoogleDeepMind into @ensembl, @uniprot & the AlphaFold database. ebi.ac.uk/about/news/tec…
Gemini 1.5 Pro - A highly capable multimodal model with a 10M token context length Today we are releasing the first demonstrations of the capabilities of the Gemini 1.5 series, with the Gemini 1.5 Pro model. One of the key differentiators of this model is its incredibly long…
Thrilled to share #Lyria, the world's most sophisticated AI music generation system. From just a text prompt Lyria produces compelling music & vocals. Also: building new Music AI tools for artists to amplify creativity in partnership w/YT & music industry deepmind.google/discover/blog/…