The impact of noise and missing fragmentation cleavages on de novo peptide identification algorithms.

ABSTRACT: Proteomics aims to characterise system-wide protein expression and typically relies on mass-spectrometry and peptide fragmentation, followed by a database search for protein identification. It has wide ranging applications from clinical to environmental settings and virtually impacts on every area of biology. In that context, de novo peptide sequencing is becoming increasingly popular. Historically its performance lagged behind database search methods but with the integration of machine learning, this field of research is gaining momentum. To enable de novo peptide sequencing to realise its full potential, it is critical to explore the mass spectrometry data underpinning peptide identification. In this research we investigate the characteristics of tandem mass spectra using 8

SUBMITTER: McDonnell K 

PROVIDER: S-EPMC8956878 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature