4 papers
Transformer-Based Active Learning for Data-Efficient Vaccine Epitope Selection in PRRS
Aspen Erlandsson Brisebois, Zahed Khatooni, Connor Burbridge +5
High-fidelity molecular docking simulations can produce biologically relevant estimates of epitope-receptor binding affinity but are computationally expensive and therefore limit t…
Exploring the Effects of Entanglement on Quantum Machine Learning of Pathogen Epitope-Receptor Binding
Aspen Erlandsson Brisebois, Luis Pablo Gonzalez Dominguez, Shivansi Prajapati +8
Parameterized quantum circuits (PQCs) provide a flexible substrate for hybrid quantum machine learning (QML), but their practical value on Noisy Intermediate-Scale Quantum (NISQ) d…
Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models
Pranta Saha, Joyce Reimer, Brook Byrns +5
The use of generative artificial intelligence (AI) models is becoming ubiquitous in many fields. Though progress continues to be made, general purpose large language AI models (LLM…
GPU-accelerated Modeling of Biological Regulatory Networks
Joyce Reimer, Pranta Saha, Chris Chen +4
The complex regulatory dynamics of a biological network can be succinctly captured using discrete logic models. Given even sparse time-course data from the system of interest, prev…