Berlin 2024 – scientific programme

Parts | Days | Selection | Search | Updates | Downloads | Help

BP: Fachverband Biologische Physik

BP 10: Computational Biophysics II

BP 10.8: Talk

Tuesday, March 19, 2024, 11:45–12:00, H 0112

Next-Gen Protein Sequencing with Nanopores Empowered by Machine Learning — •Julian Hoßbach and Christian Holm — Institute for Computational Physics, University of Stuttgart, D-70569 Stuttgart, Germany

In the last decade, the rise of DNA sequencing using nanopores has garnered significant attention within the scientific community, however, protein sequencing continues to pose substantial challenges. Recent investigations using the aerolysin nanopore have demonstrated that the discrimination of oligopeptides on a single amino acid basis is possible (Ouldali et. al, Nat. Biotechnol. 2020). Building on these advancements, our study showcases the use of machine learning to identify peptides that have thus far been undistinguishable. Our approach marks a pivotal step towards overcoming the complexities associated with protein sequencing, offering a pathway to more accurate and efficient analyses in the realm of molecular biology.

Keywords: Machine Learning; Nanopores; Protein; Sequencing