| The amino acid sequence of a protein has to be determined in order to solve its structure and function. De novo sequencing is a process where peptide sequences are derived from the mass / charge ratios of their fragments as shown on a tandem mass spectrum. When performing de novo sequencing, no protein sequence database is used for reference. In this thesis we present a method for de novo peptide sequencing based on a hidden Markov model. Experiments show that this approach is highly effective, predicting the most likely sequence and scores the accuracy of the prediction. |
