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One more time for the people in the back 🗣️

Very proud to have been part of the GenPlasmid team led by Will. Great write-up on the project 👇

A central mistake in biology was to name genes. This over-simplification made reconciling what is happening on the molecular level a mess - it's not rare to find reports of opposite mechanisms in different contexts, claimed involvement in dozens if not hundreds of different

Find me on 🦋! @ aaronwtr

The Machine Learning community moved to Bluesky, and I haven't seen a place with so many ML/AI technical conversations since Twitter 2021. For all I know, these same conversations might be happening here in X, but the algorithm decided not to show them to me anymore.

1️⃣ "PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction” Aaron Wenteler Martina Occhetta biorxiv.org/content/10.110…

I spoke with nature about the transformative potential of foundation models for biology—particularly in personalized medicine and clinical diagnostics. Take a look at the technologies to watch in 2025. An exciting year ahead in AI, biology and medicine! nature.com/articles/d4158…

It was a pleasure talking about our recent single-cell foundation model benchmark, PertEval-scFM, at the Multiomics Reading Group at Mila - Institut québécois d'IA. Many thanks to the organizers for the invitation and to Valence Labs for sharing the talk youtu.be/DCezfwQkkAE?si…

🔬 How well do single-cell foundation models (scFMs) predict perturbation effects? This study introduces PertEval-scFM, a benchmark evaluating zero-shot scFM embeddings against simpler baseline models to assess their effectiveness in predicting transcriptional responses to

Am I the only one who feels GPT 4.5 is actually worse than 4o? Its prompt adherence seems to be bad in my experience. Thought that might be beneficial for creative tasks, but even there, I feel like the outputs it generates are underwhelming compared to 4o

Congrats Ajay Nadig on TRADE out now in Nature Genetics: nature.com/articles/s4158… These statistical metrics enable more meaningful comparisons in Perturb-seq atlases. Also, now find the HepG2 and Jurkat Perturb-seq datasets on GEO GSE264667!

Proud to share that PertEval-scFM got accepted into ICML! Hope to see you all in Vancouver. 🇨🇦

Deep-learning at scale is so complicated engineering-wise that assessing the value of a new idea without an army of top-notch colleagues to help you is IMO impossible.

University budgets everywhere are getting slashed, and we hear many PhD students with accepted ICML papers can no longer afford to attend. We are stepping in to offer travel grants for researchers who lost funding. Sponsored by Pillar VC, Ormoni Bio, Latent Labs, and Cimulate

Uni of Adelaide Charles Darwin University How is AI driving drug discovery? Listen to Aaron Wenteler as he explains how #AI and #MachineLearning can sift through the data to refine drug targets. Read more in #CPPrecisionmedicine: AI approaches for the discovery and validation of drug targets ➡️bit.ly/3XlAWpL