9 citations · 10 across the 2 of their papers we have counts for
4 papers
Multi-state Protein Design with DynamicMPNN
Alex Abrudan, Sebastian Pujalte Ojeda, Chaitanya K. Joshi +6
Structural biology has long been dominated by the one sequence, one structure, one function paradigm, yet many critical biological processes - from enzyme catalysis to membrane tra…
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)…
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…