8 citations · 10 across the 3 of their papers we have counts for
3 papers
SEISMO: Explanation-Aware, Trajectory-Conditioned LLM Agents for Sample-Efficient Molecular Optimisation
Fabian P. Krüger, Andrea Hunklinger, Adrian Wolny +3
Optimizing molecules to achieve desired properties is a central bottleneck across the chemical sciences, particularly in the pharmaceutical industry, where it underlies the discove…
Toward the Explainability of Protein Language Models
Andrea Hunklinger, Noelia Ferruz
Protein language models (pLMs) excel in a variety of tasks that range from structure prediction to the design of functional enzymes. However, these models operate as black boxes, a…
Reinforcement Learning Guides Generative Protein Language Models
Filippo Stocco, Maria Artigues-Lleixa, Andrea Hunklinger +4
Protein engineering can optimize molecules for biotechnology and therapeutics, but navigating the high-dimensional sequence landscape remains challenging. Protein language models (…