4 papers
PepCompass: Navigating peptide embedding spaces using Riemannian Geometry
Marcin Możejko, Adam Bielecki, Jurand PrÄ dzyÅski +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…
Sample Efficient Generative Molecular Optimization with Joint Self-Improvement
Serra Korkmaz, Adam Izdebski, Jonathan Pirnay +5
Generative molecular optimization aims to design molecules with properties surpassing those of existing compounds. However, such candidates are rare and expensive to evaluate, yiel…
seqme: a Python library for evaluating biological sequence design
Rasmus Møller-Larsen, Adam Izdebski, Jan Olszewski +4
Recent advances in computational methods for designing biological sequences have sparked the development of metrics to evaluate these methods performance in terms of the fidelity o…
ProSpero: Active Learning for Robust Protein Design Beyond Wild-Type Neighborhoods
Michal Kmicikiewicz, Vincent Fortuin, Ewa Szczurek
Designing protein sequences of both high fitness and novelty is a challenging task in data-efficient protein engineering. Exploration beyond wild-type neighborhoods often leads to…