Beam search decoder for enhancing sequence decoding speed in single-molecule peptide sequencing data

Abstract

Next-generation single-molecule protein sequencing technologies have the potential to accelerate biomedical research significantly. These technologies offer sensitivity and scalability for proteomic analysis. One auspicious method is fluorosequencing, which involves: cutting naturalized proteins into peptides, attaching fluorophores to specific amino acids, and observing variations in light intensity as one amino acid is removed at a time. The original peptide is classified from the sequence of light-intensity reads, and proteins can subsequently be recognized with this information. The amino acid step removal is achieved by attaching the peptides to a wall on the C-terminal and using a process called Edman Degradation to remove an amino acid from the N-Terminal. Even though a framework (Whatprot) has been proposed for the peptide classification task, processing times remain restrictive due to the massively parallel data acquisicion system. In this paper, we propose a new beam search decoder with a novel state formulation that obtains much lower processing times with slightly higher accuracies than Whatprot. Furthermore, we explore how our novel state formulation may lead to even faster decoders in the future.