Valence Labs

We are livestreaming the talks from the Molecular Machine Learning Conference today! Jian Tang is live now discussing geometric deep learning for protein understanding. Tune in here: https://lnkd.in/g3YdxZpv You can find the schedule for the rest of the day below. 10:35 AM - Cas Wognum: "Polaris: An industry-led initiative to critically assess machine learning for real-world drug discovery" 1:15 PM - Jason Hartford: "Efficiently Detecting Interactions From High Dimensional Observations of Pairwise Perturbations" 1:55 PM - Raquel Rodríguez-Pérez: "Leveraging Molecular ML & Property Prediction in Drug Design" 3:35 PM - Max Jaderberg: "Towards Rational Drug Design with AlphaFold 3" More details here: https://lnkd.in/gVK7nFaq

Day 1 of the ML for Drug Discovery Summer School was awesome! 🏫 Over 150 people were in attendance to learn from speakers like Bharath Ramsundar, Emmanuel Noutahi, PhD, Dominique Beaini, and Mario Geiger. Topics covered included: GNNs, virtual screening, molecular representation and scoring, and more. Building on the concepts taught in the lectures, Cas Wognum and Lu Zhu finished the day with a hands-on lab on virtual screening. Students used datasets of 2D molecules to develop predictive models for assessing inhibitory activity against EGFR! 🧪 Day 2 starts tomorrow at 8:30 AM with a talk on ML in Structure-Based Drug Discovery by Gabriele Corso. See the full schedule for the Summer School here: https://lnkd.in/gvUG-848

We are very excited to have Alán Aspuru-Guzik join us for a special edition of M2D2 to discuss the growing field of self-driving labs for chemistry, materials science, and biotech. Tune in live this Thursday, May 30th from 11am - 12pm ET: https://lnkd.in/gaYs7nqy

🚀Join us for the 2nd Activator Deep Dive Session next week: Hosted by IQ Capital and Valence Labs - Learn about next-gen sequencing tech from a panel of leaders from Tagomics, Caeruleus Genomics, Oxford Nanopore Technologies, and Valence Labs 🗓 WHEN: May 28th 6:30 - 9:30 PM 📍 WHERE: London 🔗 Register Now - https://lu.ma/xfa8h525 Thanks to our sponsors IQ Capital & Valence Labs! 

May 16th is the new date for our TechBio Meetup at Stanford University with the Stanford Biotechnology Group. Join us on Thursday starting at 6 pm PT. Berton Earnshaw will be there to give an overview of Valence Labs and our research directions. We’ll also hear from Eric Nguyen on Evo, a long-context biological foundation model. There are only a few spots left, RSVP here: https://lnkd.in/gXDD-T-a

Can GNNs scale? This question has divided the community for years. For the first time, we observe that GNNs benefit tremendously from the increasing width, number of molecules, number of labels, and diversity in the pretraining datasets. With these findings, we introduce MolGPS - a 1B parameter model for molecular property prediction. Read the blog here: https://lnkd.in/gXymSrv9 Learn more about MolGPS at the DMLR Workshop at ICLR 2024 on Saturday, May 11th with Valence Labs scientists Maciej Sypetkowski, Frederik Wenkel, and Dominique Beaini. For more details, read the full paper “On the Scalability of GNNs for Molecular Graphs": https://lnkd.in/gFQ-C8-t

The Valence Labs team is heading to ICLR 2024 and we’re hosting a TechBio social! Join us and the TechBio community on Wednesday, May 8th. RSVP here: https://lu.ma/107e2us0 Our team will also be presenting papers throughout the conference. See below for a summary 👇 -- “Object-centric architectures enable efficient causal representation learning” Where: Poster Session 2 - Halle B #217 When: Tues, May 7th from 4:30 pm - 6:30 pm Schedule link: https://lnkd.in/ghV6xYPW Paper: https://lnkd.in/gHerHHE4 Jason Hartford “Local Search GFlowNets” Where: Poster Session 3 - Halle B #177 When: Weds, May 8th from 10:45 am - 12:45 pm Schedule link: https://lnkd.in/gGVn8JwP Paper: https://lnkd.in/gisQVvvr Emmanuel Bengio “Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets” Where: Poster Session 3 - Halle B #5 When: Weds, May 8th from 10:45 am - 12:45 pm Schedule link: https://lnkd.in/gj86FMKN Paper: https://lnkd.in/ehGZVXS2 Dominique Beaini, Frederik Wenkel, and Maciej Sypetkowski “Active learning to discover pairwise genetic interactions via representation learning” Where: MLGenX (Lehar 1) and the Generative and Experimental Perspectives for Biomolecular Design (Halle A2) Workshops When: Sat, May 11th at 9 am Schedule link: https://www.gembio.ai/ Paper: https://lnkd.in/gsaDsquG Jason Hartford “Propensity Score Alignment for Unpaired Multimodal Data” Where: MLGenX Workshop - Lehar 1 When: Sat, May 11th at 9 am Schedule link: https://mlgenx.github.io/ Paper: https://lnkd.in/gv-fErT5 Jason Hartford “On the Scalability of GNNs for Molecular Graphs” Where: Data-centric Machine Learning Research (DMLR) Workshop - Stolz 2 When: Sat, May 11th at 9 am Schedule link: https://dmlr.ai// Paper: https://lnkd.in/gFQ-C8-t Maciej Sypetkowski, Frederik Wenkel, and Dominique Beaini

We’re hosting a TechBio meetup at Stanford University with the Stanford Biotechnology Group on April 22nd! Join us for a fun evening of discussions about AI x drug discovery, food, drinks, and a talk from Brian Hie on Evo. Register for the event on Portal here: https://lnkd.in/gbVYp-aR Our team is also growing. Come and work with us to push the frontier of AI-enabled drug discovery. We are hiring ML Engineers, Research Scientists, Research Engineers, and more across our Montreal and London offices. Apply now: https://lnkd.in/g9h5beuK

This will be a great opportunity to get hands-on training from professors worldwide covering everything from the fundamentals to the latest advances in machine learning for drug discovery. Register below!

This will be a great opportunity to get hands-on training from professors worldwide covering everything from the fundamentals to the latest advances in machine learning for drug discovery. Register below!