Researches On B/Y Peak Selecting Algorithm Based On Support Vector Machine Classification And Peptide Sequence Tag Generating Algorithm

Proteomics is an increasingly powerful and indispensable technology in molecular cell biology. It can be used to identify the components of small protein complexes and large organelles, to determine post-translational modifications and in sophisticated functional screens. Biological mass spectrometry technology is the critical fundamental of mass-spectrometry-based proteomics, the key step in which the peptide sequencing is the key step. Peptide sequencing algorithms used to date include database search, de novo sequencing and peptide sequence tag based database search, the first important step of which is peak filtering related to computational complexity. Peak selecting achieved excellent results in tandem mass spectrometry data with high mass precise rather than that of low mass precise.Our research built an algorithm based on support vector machine classification to select peaks only assigned as "b/y ions" in tandem mass spectrometry data with low mass precise, which could reduce the computational complexity of the spectrum graph constructing and peptide sequence tag generating and improve the reliability of peptide sequence tags.Our research was mainly based on the following hypothesis.1. All peaks used to construct a spectrum graph are b or y ions.2. b/y ions have isotopes and neutral losses such as -H₂O, -NH₃, -H₂O-H₂O, -H₂O -NH3, while noises have no such ramifications.3. Difference between b/y ions and other fragments from peptide collision is the existence or absence of complementarities.In order to verify the method of b/y ions selecting, we trained and then tested the model by one data set of a control sample (1281 spectra). The algorithm was compared to popular methods used nowadays, and the results showed that our method had an advantage of simplifying the computational complexity of spectrum graph constructing and peptide sequence tag generating.The results of our b/y peak selecting algorithm were then applied to the consequent research for generation of peptide sequence tags. The peptide sequence tags generated from our algorithm performed a similar accuracy with PepNovoTag, a fairly well software in this field and both of them achieved a better accuracy than that of GutenTag.