1 citations · 1 across the 4 of their papers we have counts for
4 papers
FoldSAE: Learning to Steer Protein Folding Through Sparse Representations
Wojciech Zarzecki, Paulina Szymczak, Ewa Szczurek +1
RFdiffusion is a popular and well-established model for generation of protein structures. However, this generative process offers limited insight into its internal representations…
PepCompass: Navigating peptide embedding spaces using Riemannian Geometry
Marcin Możejko, Adam Bielecki, Jurand Prądzyński +10
Antimicrobial peptide discovery is challenged by the astronomical size of peptide space and the relative scarcity of active peptides. Generative models provide continuous latent "m…
OmegAMP: Targeted AMP Discovery via Biologically Informed Generation
Diogo Soares, Leon Hetzel, Paulina Szymczak +6
Deep learning-based antimicrobial peptide (AMP) discovery faces critical challenges such as limited controllability, lack of representations that efficiently model antimicrobial pr…
Artificial intelligence-driven antimicrobial peptide discovery
Paulina Szymczak, Ewa Szczurek
Antimicrobial peptides (AMPs) emerge as promising agents against antimicrobial resistance, providing an alternative to conventional antibiotics. Artificial intelligence (AI) revolu…