Protein Sequencing with an Adaptive Genetic Algorithm from Tandem Mass Spectrometry

preprint · arXiv · 2008

preprint · arXiv · 2008. Jean-Charles Boisson et al. In Proteomics, only the de novo peptide sequencing approach allows a partial amino acid sequence of a peptide…
Date 2008-04-08
Type preprint
Venue arXiv
Publisher arXiv
Contribution algorithm
DOI 10.48550/arXiv.0804.1201
Citations (OpenAlex) 0

Abstract

In Proteomics, only the de novo peptide sequencing approach allows a partial amino acid sequence of a peptide to be found from a MS/MS spectrum. In this article a preliminary work is presented to discover a complete protein sequence from spectral data (MS and MS/MS spectra). For the moment, our approach only uses MS spectra. A Genetic Algorithm (GA) has been designed with a new evaluation function which works directly with a complete MS spectrum as input and not with a mass list like the other methods using this kind of data. Thus the mono isotopic peak extraction step which needs a human intervention is deleted. The goal of this approach is to discover the sequence of unknown proteins and to allow a better understanding of the differences between experimental proteins and proteins from databases.

Authors

  1. Jean-Charles Boisson · LIFL / INRIA
  2. Laetitia Jourdan · LIFL / INRIA
  3. El-Ghazali Talbi · LIFL / INRIA
  4. Christian Rolando · Université Lille 1

Methods and tools

  • Adaptive GA for tandem-MS peptide sequencing: Adaptive genetic algorithm for protein sequencing from tandem MS. Represents peptides as GA individuals, evolves them against the observed spectrum; the adaptive component tunes mutation / crossover rates on the fly.

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