Lack of data has hampered the building of models to accurately predict binding affinity so I’m sure everyone is super excited to see the first
Tag: artificial intelligence
An interesting way to look for better biological foundation models. The core bet is simple: biological data is expensive. Text and image models often improve
A recent paper on ChemRxiv https://chemrxiv.org/doi/10.26434/chemrxiv-2025-9c1v6 describes ANNalog a transformer-based sequence-to-sequence generative model trained on pairs of molecules extracted from the same bioactivity assay in
A while back Apple published a paper entitled LLM in a flash: Efficient Large Language Model Inference with Limited Memory [DOI] This paper tackles the
The next OpenADMET blind challenge focuses on predicting human Pregnane-X Receptor (hPXR) induction. The pregnane X receptor (hPXR) is the major determinant of CYP3A gene regulation by
OpenFold3-preview is a biomolecular structure prediction model aiming to be a bitwise reproduction of DeepMind’sAlphaFold3, developed by the AlQuraishi Lab at Columbia University and the
AI/ML have reignited our thoughts on how we represent chemical structures and so it is very timely that we have a conference on Structural Representation.
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.
UK Research and Innovation (UKRI) has announced a £76 million investment to launch four new national compute resources (NCRs). The funding covers both equipment and
Well it was standing room only at the last nights Cambridge Cheminformatics Network meeting Co-folding special. Many thanks to all the speakers I’m sorry we