This looks like an amazing opportunity. Apply to lead a strategic research lab dedicated to advancing the UK’s position in fundamental artificial intelligence (AI) development.
Tag: machine learning
An interesting web app that fetches ChEMBL bioactivity data for a target (via UniProt ID), computes molecular descriptors, and trains a simple predictive model (regression, with
Prediction of the metabolism of small molecules is very challenging and so having a variety of different tools is always useful. I’ve previously written Vortex
PROteolysis TArgeting Chimeras (PROTACs) technology provides an alternative to module biological function by specially using the ubiquitin proteasome system to induce degradation of the target
Next up Date: 5 February 2026 Lecture Theatre, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge CB2 0AW. No need to register in advance – just
I’ve reviewed TabPFN in the past. https://macinchem.org/2025/02/06/looking-at-tabpfn and I noticed there was a recent update. TabPFN is a foundation model trained on around 130,000,000 synthetically generated
OpenADMET have just announced the ExpansionRx-OpenADMET blind challenge in partnership with Expansion Therapeutics. Expansion Therapeutics have decided to make all the ADMET publicly available. “We
TabPFN is a foundation model trained on around 130,000,000 synthetically generated datasets that mimic “real world” tabular data. These datasets sampled dataset size and number
A recent paper published in Nature caught my eye, Accurate predictions on small data with a tabular foundation model by Hollmann et al., Here we present