13 citations · 13 across the 6 of their papers we have counts for
6 papers
Efficient Auto-Interpretability of AI Models in Biology
Piotr Jedryszek, Oliver M. Crook
Sparse autoencoders (SAEs), and other interpretability methods could turn AI models in Biology and other fields into engines of scientific discovery by explaining the superhuman ca…
Probing and steering biology across Boltz-1s trunk-diffusion boundary
Piotr Jedryszek, Tongmeng Xie, Adam Winnifrith +5
AlphaFold3-class structure predictors pair a representational trunk, which processes sequence and context, with a diffusion module, which generates atomic coordinates. How biologic…
Retrieval and competition: how a protein foundation model starts a protein
Piotr Jedryszek, Oliver M. Crook
Protein language models are increasingly used to guide experimental and clinical decisions, yet it is often unclear whether a confident prediction reflects recognition of biologica…
Analysis of the first Genetic Engineering Attribution Challenge
Oliver M. Crook, Kelsey Lane Warmbrod, Greg Lipstein +8
The ability to identify the designer of engineered biological sequences -- termed genetic engineering attribution (GEA) -- would help ensure due credit for biotechnological innovat…
Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics
Oliver M. Crook, Kathryn S. Lilley, Laurent Gatto +1
Understanding sub-cellular protein localisation is an essential component to analyse context specific protein function. Recent advances in quantitative mass-spectrometry (MS) have…
Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics
Oliver M. Crook, Laurent Gatto, Paul D. W. Kirk
The Dirichlet Process (DP) mixture model has become a popular choice for model-based clustering, largely because it allows the number of clusters to be inferred. The sequential upd…