9 citations · 13 across the 4 of their papers we have counts for
4 papers
IgCraft: A versatile sequence generation framework for antibody discovery and engineering
Matthew Greenig, Haowen Zhao, Vladimir Radenkovic +2
Designing antibody sequences to better resemble those observed in natural human repertoires is a key challenge in biologics development. We introduce IgCraft: a multi-purpose model…
Understanding Biology in the Age of Artificial Intelligence
Elsa Lawrence, Adham El-Shazly, Srijit Seal +6
Modern life sciences research is increasingly relying on artificial intelligence approaches to model biological systems, primarily centered around the use of machine learning (ML)…
Improving Antibody Humanness Prediction using Patent Data
Talip Ucar, Aubin Ramon, Dino Oglic +3
We investigate the potential of patent data for improving the antibody humanness prediction using a multi-stage, multi-loss training process. Humanness serves as a proxy for the im…
Score-Based Generative Models for Designing Binding Peptide Backbones
John D Boom, Matthew Greenig, Pietro Sormanni +1
Score-based generative models (SGMs) have proven to be powerful tools for designing new proteins. Designing proteins that bind a pre-specified target is highly relevant to a range…