1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
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…
q-bio.BM2023★ 1 cited
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…
cs.LG2022
A generative recommender system with GMM prior for cancer drug generation and sensitivity prediction
Krzysztof Koras, Marcin Możejko, Paulina Szymczak +2
Recent emergence of high-throughput drug screening assays sparkled an intensive development of machine learning methods, including models for prediction of sensitivity of cancer ce…