QubitONeuronPrivate Limited
QubitONeuronPrivate Limited
We work across molecular bioinformatics, quantum-inspired learning and specialised compute, developing new ways to search biological sequence space. The direction of the research is public. The implementation stays in the lab.
We map iterative scientific and optimisation workloads onto reconfigurable silicon, targeting predictable low latency and far better energy efficiency than a general purpose processor gives us for the same work.
We study antimicrobial peptide sequence space through the physicochemical properties that govern how a short peptide behaves at a bacterial membrane. Our current focus is charge-aware screening: finding activity-relevant patterns in sequence, then prioritising candidates for deeper computational and experimental evaluation.
Current frontier: antimicrobial peptide screening and candidate prioritisation
Research screening only. Not a clinical or therapeutic decision system.
We investigate hybrid models that borrow structure from quantum systems to learn nonlinear relationships in peptide data. Every quantum operation is simulated on classical hardware and integrated with conventional machine learning. We do not claim access to quantum hardware, and we do not need it for this work.
Research direction, scope and scientific reasoning are open. Detailed architecture, benchmarks and validation data are shared with collaborators, partners and investors under agreement.
If you invest in deep tech, run a lab, or want to build this with us, we would like to hear from you.